https://models.pbl.nl/api.php?action=feedcontributions&feedformat=atom&user=JoeriOostenrijk 2026-04-25T20:06:39Z User contributions MediaWiki 1.39.15 https://models.pbl.nl/index.php?title=Energy_conversion/Description&diff=21530 2014-05-08T16:40:33Z

<p>JoeriOostenrijk: </p> <hr /> <div>{{ComponentDescriptionTemplate<br /> |Reference=Hoogwijk, 2004; Van Vuuren, 2007; Hendriks et al., 2004b; Van Ruijven et al., 2007;<br /> |Description=[[TIMER model|TIMER]] includes two main energy conversion modules: Electric power generation and hydrogen generation. Below, electric power generation is described in detail. In addition, the key characteristics of the hydrogen generation model, which follows a similar structure, are presented.<br /> <br /> ==Electric power generation==<br /> As shown in the flowchart, two key elements of the electric power generation are the investment strategy and the operational strategy in the sector. A challenge in simulating electricity production in an aggregated model is that in reality electricity production depends on a range of complex factors, related to costs, reliance, and the time required to switch on technologies. Modelling these factors requires a high level of detail and thus {{AbbrTemplate|IAM}}s) such as [[TIMER model|TIMER]] concentrate on introducing a set of simplified, meta relationships ([[Hoogwijk, 2004]]; [[Van Vuuren, 2007]]).<br /> <br /> ===Total demand for new capacity===<br /> The electricity capacity required to meet the demand per region is based on a forecast of the maximum electricity demand plus a reserve margin of about 10% (including the capacity credit assigned to different forms of electricity generation). Maximum demand is calculated on the basis of an assumed monthly shape of the load duration curve (LDC) and the gross electricity demand. The latter comprises the net electricity demand from the end-use sectors plus electricity trade and transmission losses ({{AbbrTemplate|LDC}}) accounts for characteristics such as cooling and lighting demand). The demand for new generation capacity is the difference between the required and existing capacity. Power plants are assumed to be replaced at the end of their lifetime, which varies from 30 to 50 years, depending on the technology and is currently fixed in the model.<br /> <br /> ===Decisions to invest in specific options ===<br /> In the following step, a decision is made to invest in different generation technologies. In the model, this is done on the basis of the price of electricity (in USD/kWhe) produced per technology, using a multinomial logit equation that assigns larger market shares to the lower cost options. The specific costs of each option is broken down into a number of categories: investment or capital costs (USD/kWe), fuel costs (USD/GJ), operational and maintenance costs (OM) and other costs (see further). An exception is hydropower capacity, which is exogenously prescribed, because large hydropower plants often have functions other than only electricity production (e.g. water supply and flood control). In the equations, some constraints are added to account for limitations in supply (e.g. restrictions on biomass availability). The investments needed for each option are given in the form of total investment in new generation capacity and the share of each individual technology (determined on the basis of price and preference).<br /> <br /> ===Operational strategy===<br /> Use of power plants is based on operational costs, with low-cost technologies assumed to be used most often. This implies that capital-intensive plants with low operational costs, such as renewable and nuclear energy, operate as many hours as possible. To some degree, this is also true for other plants with low operational costs, such as coal. <br /> The operational decision is presented in the following three steps:<br /> #Renewable sources PV and wind are assigned, followed by hydropower, because these options have the lowest operational costs;<br /> #The peak load capacity (period of high electricity demand) is assigned on the basis of the operational costs of each available plant and the ability of these plants to provide peak load capacity; <br /> #Base load (period of medium to low energy demand) is assigned on the basis of the remaining capacity (after steps 1 and 2), operational costs and the ability of options to provide the base load capacity.<br /> <br /> <br /> ===Fossil-fuel and bio-energy power plants===<br /> A total of 20 types of power plants generating electricity using fossil fuels and bioenergy are included. These power plants represent different combinations of conventional technology, such as gasification and combined cycle (CC) technology; combined heat and power (CHP); and carbon capture and storage (CCS;([[Hendriks et al., 2004b]]). The specific capital costs and thermal efficiencies of these types of plants are determined by exogenous assumptions that describe the technological progress of typical components of these plants:<br /> *For conventional power plants, the coal-fired plant is defined in terms of overall efficiency and investment cost. The characteristics of all other conventional plants (using oil, natural gas or bioenergy) are described in the investment differences for desulphurisation, fuel handling and efficiency.<br /> *For Combined Cycle (CC) power plants, the characteristics of a natural gas fired plant are set as the standard. Other CC plants (fuelled by oil, bioenergy and coal after gasification) are defined by indicating additional capital costs for gasification, efficiency losses due to gasification, and operation and maintenance (O&amp;M) costs for fuel handling. <br /> *Power plants with carbon-capture-and-storage systems (CCS) are assumed to be CC plants, but with fuel-specific lower efficiency and higher investment and O&amp;M costs (related to capture and storage). <br /> *The characteristics of combined-heat-and-power plants (CHP) are similar to those of other plants, but with an assumed small increase in capital costs, in combination with a lower efficiency for electric conversion and an added factor for heat efficiency. <br /> <br /> The cost of one unit electricity generated is equal to the sum of the capital cost, operational and maintenance costs (O&amp;M), fuel cost, and CO2 storage cost.<br /> <br /> ===Solar and wind power===<br /> <br /> The costs of solar and wind power in the model are determined by learning and depletion dynamics. For renewable energy, costs relate to capital, O&amp;M and system integration. The capital costs mostly relate to learning and depletion processes. Learning is represented by in learning curves (see flowchart); depletion is by long-term in cost–supply curves. <br /> <br /> The additional system integration costs relate to curtailed electricity (if production exceeds demand and the overcapacity cannot be used within the system), backup capacity; and additional required spinning reserve. The last items are needed to avoid loss of power if the supply of wind or solar power drops suddenly, enabling a power scale up in a relatively short time, in power stations operating below maximum capacity ([[Hoogwijk, 2004]]).<br /> <br /> To determine curtailed electricity, the model compares 10 points on the load-demand curve at the overlap between demand and supply. For both wind and solar power, a typical load supply curve is assumed (see [[Hoogwijk, 2004]]). If supply exceeds demand, the overcapacity in electricity is assumed to be discarded, resulting in higher production costs.<br /> <br /> Because wind and solar power supply is intermittent (variable and thus not reliable), the model assumes that backup capacity needs to be installed. It is assumed that no backup is required for first 5% penetration of the intermittent capacity. However, for higher levels of penetration, the effective capacity (degree to which operators can rely on plants producing at a specific time) of intermittent resources is assumed to decrease. This is referred to as the capacity factor. This decrease leads to the need for backup power by low-cost options, such as gas turbines, the cost of which is allocated to the intermittent source.<br /> <br /> The required spinning reserve of the power system is the capacity that can be used to respond to a rapid increase in demand. This is assumed to be 3.5% of the installed capacity of a conventional power plant. If wind and solar power further penetrate the market, the model assumes an additional, required spinning reserve of 15% of the intermittent capacity (after subtraction of the 3.5% existing capacity). The related costs are allocated to the intermittent source.<br /> <br /> ===Nuclear power===<br /> The costs of nuclear power also include capital, O&amp;M and nuclear fuel costs. Similar to the renewable energy options, technology improvement in nuclear power is described via a learning curve (costs decrease with cumulative installed capacity). Fuel costs increase as a function of depletion. Fuel costs are determined on the basis of the estimated extraction costs for uranium and thorium resources, see [[Energy Supply]]. A small trade model for these fission fuels is included..<br /> <br /> ==Hydrogen generation model==<br /> The structure of the hydrogen generation submodule is similar to that for electric power generation ([[Van Ruijven et al., 2007]]) but with following differences:<br /> *There are only eleven supply options for hydrogen production coal, oil, natural gas and bioenergy, with and without carbon capture and storage (8 plants); hydrogen production from electrolysis, direct hydrogen production from solar thermal processes; and small methane reform plants. <br /> *No description of preferences for different power plants is taken into account in the operational strategy. The load factor for each option equals the total production divided by the capacity for each region.<br /> *Intermittence does not play an important role because hydrogen can be stored to some degree. Thus, there are no equations simulating system integration.<br /> *Hydrogen can be traded. A trade model is added, similar to those for fossil fuels described in [[Energy supply]].<br /> }}</div>

JoeriOostenrijk https://models.pbl.nl/index.php?title=Energy_conversion/Description&diff=21529 2014-05-08T16:40:04Z

<p>JoeriOostenrijk: </p> <hr /> <div>{{ComponentDescriptionTemplate<br /> |Reference=Hoogwijk, 2004; Van Vuuren, 2007; Hendriks et al., 2004b; Van Ruijven et al., 2007;<br /> |Description=[[TIMER model|TIMER]] includes two main energy conversion modules: Electric power generation and hydrogen generation. Below, electric power generation is described in detail. In addition, the key characteristics of the hydrogen generation model, which follows a similar structure, are presented.<br /> <br /> ==Electric power generation==<br /> As shown in the flowchart, two key elements of the electric power generation are the investment strategy and the operational strategy in the sector. A challenge in simulating electricity production in an aggregated model is that in reality electricity production depends on a range of complex factors, related to costs, reliance, and the time required to switch on technologies. Modelling these factors requires a high level of detail and thus {{AbbrTemplate|IAM}}s) such as [[TIMER model|TIMER]] concentrate on introducing a set of simplified, meta relationships ([[Hoogwijk, 2004]]; [[Van Vuuren, 2007]]).<br /> <br /> ===Total demand for new capacity===<br /> The electricity capacity required to meet the demand per region is based on a forecast of the maximum electricity demand plus a reserve margin of about 10% (including the capacity credit assigned to different forms of electricity generation). Maximum demand is calculated on the basis of an assumed monthly shape of the load duration curve (LDC) and the gross electricity demand. The latter comprises the net electricity demand from the end-use sectors plus electricity trade and transmission losses ({{AbbrTemplate|LDC}}) accounts for characteristics such as cooling and lighting demand). The demand for new generation capacity is the difference between the required and existing capacity. Power plants are assumed to be replaced at the end of their lifetime, which varies from 30 to 50 years, depending on the technology and is currently fixed in the model.<br /> <br /> ===Decisions to invest in specific options ===<br /> In the following step, a decision is made to invest in different generation technologies. In the model, this is done on the basis of the price of electricity (in USD/kWhe) produced per technology, using a multinomial logit equation that assigns larger market shares to the lower cost options. The specific costs of each option is broken down into a number of categories: investment or capital costs (USD/kWe), fuel costs (USD/GJ), operational and maintenance costs (OM) and other costs (see further). An exception is hydropower capacity, which is exogenously prescribed, because large hydropower plants often have functions other than only electricity production (e.g. water supply and flood control). In the equations, some constraints are added to account for limitations in supply (e.g. restrictions on biomass availability). The investments needed for each option are given in the form of total investment in new generation capacity and the share of each individual technology (determined on the basis of price and preference).<br /> <br /> ===Operational strategy===<br /> Use of power plants is based on operational costs, with low-cost technologies assumed to be used most often. This implies that capital-intensive plants with low operational costs, such as renewable and nuclear energy, operate as many hours as possible. To some degree, this is also true for other plants with low operational costs, such as coal. <br /> The operational decision is presented in the following three steps:<br /> #Renewable sources PV and wind are assigned, followed by hydropower, because these options have the lowest operational costs;<br /> #The peak load capacity (period of high electricity demand) is assigned on the basis of the operational costs of each available plant and the ability of these plants to provide peak load capacity; <br /> #Base load (period of medium to low energy demand) is assigned on the basis of the remaining capacity (after steps 1 and 2), operational costs and the ability of options to provide the base load capacity.<br /> <br /> <br /> ===Fossil-fuel and bio-energy power plants===<br /> A total of 20 types of power plants generating electricity using fossil fuels and bioenergy are included. These power plants represent different combinations of conventional technology, such as gasification and combined cycle (CC) technology; combined heat and power (CHP); and carbon capture and storage (CCS;([[Hendriks et al., 2004b]]). The specific capital costs and thermal efficiencies of these types of plants are determined by exogenous assumptions that describe the technological progress of typical components of these plants:<br /> *For conventional power plants, the coal-fired plant is defined in terms of overall efficiency and investment cost. The characteristics of all other conventional plants (using oil, natural gas or bioenergy) are described in the investment differences for desulphurisation, fuel handling and efficiency.<br /> *For Combined Cycle (CC) power plants, the characteristics of a natural gas fired plant are set as the standard. Other CC plants (fuelled by oil, bioenergy and coal after gasification) are defined by indicating additional capital costs for gasification, efficiency losses due to gasification, and operation and maintenance (O&amp;M) costs for fuel handling. <br /> *Power plants with carbon-capture-and-storage systems (CCS) are assumed to be CC plants, but with fuel-specific lower efficiency and higher investment and O&amp;M costs (related to capture and storage). <br /> *The characteristics of combined-heat-and-power plants (CHP) are similar to those of other plants, but with an assumed small increase in capital costs, in combination with a lower efficiency for electric conversion and an added factor for heat efficiency. <br /> <br /> The cost of one unit electricity generated is equal to the sum of the capital cost, operational and maintenance costs (O&amp;M), fuel cost, and CO2 storage cost.<br /> <br /> ===Solar and wind power===<br /> <br /> The costs of solar and wind power in the model are determined by learning and depletion dynamics. For renewable energy, costs relate to capital, O&amp;M and system integration. The capital costs mostly relate to learning and depletion processes. Learning is represented by in learning curves (see flowchart); depletion is by long-term in cost–supply curves. <br /> <br /> The additional system integration costs relate to curtailed electricity (if production exceeds demand and the overcapacity cannot be used within the system), backup capacity; and additional required spinning reserve. The last items are needed to avoid loss of power if the supply of wind or solar power drops suddenly, enabling a power scale up in a relatively short time, in power stations operating below maximum capacity ([[Hoogwijk, 2004]]).<br /> <br /> To determine curtailed electricity, the model compares 10 points on the load-demand curve at the overlap between demand and supply. For both wind and solar power, a typical load supply curve is assumed (see [[Hoogwijk, 2004]]). If supply exceeds demand, the overcapacity in electricity is assumed to be discarded, resulting in higher production costs.<br /> <br /> Because wind and solar power supply is intermittent (variable and thus not reliable), the model assumes that backup capacity needs to be installed. It is assumed that no backup is required for first 5% penetration of the intermittent capacity. However, for higher levels of penetration, the effective capacity (degree to which operators can rely on plants producing at a specific time) of intermittent resources is assumed to decrease. This is referred to as the capacity factor. This decrease leads to the need for backup power by low-cost options, such as gas turbines, the cost of which is allocated to the intermittent source.<br /> <br /> The required spinning reserve of the power system is the capacity that can be used to respond to a rapid increase in demand. This is assumed to be 3.5% of the installed capacity of a conventional power plant. If wind and solar power further penetrate the market, the model assumes an additional, required spinning reserve of 15% of the intermittent capacity (after subtraction of the 3.5% existing capacity). The related costs are allocated to the intermittent source.<br /> <br /> ===Nuclear power===<br /> The costs of nuclear power also include capital, O&amp;M and nuclear fuel costs. Similar to the renewable energy options, technology improvement in nuclear power is described via a learning curve (costs decrease with cumulative installed capacity). Fuel costs increase as a function of depletion. Fuel costs are determined on the basis of the estimated extraction costs for uranium and thorium resources, see [[Energy Supply]]. A small trade model for these fission fuels is included..<br /> <br /> ==Hydrogen generation model==<br /> The structure of the hydrogen generation submodule is similar to that for electric power generation ([[Van Ruijven et al., 2007]]) but with following differences:<br /> *There are only eleven supply options for hydrogen production coal, oil, natural gas and bioenergy, with and without carbon capture and storage (8 plants); hydrogen production from electrolysis, direct hydrogen production from solar thermal processes; and small methane reform plants. <br /> *No description of preferences for different power plants is taken into account in the operational strategy. The load factor for each option equals the total production divided by the capacity for each region.<br /> *Intermittence does not play an important role because hydrogen can be stored to some degree. Thus, there are no equations simulating system integration.<br /> *Hydrogen can be traded. A trade model is added, similar to those for fossil fuels described in [[Energy Supply]].<br /> }}</div>

JoeriOostenrijk https://models.pbl.nl/index.php?title=Energy_conversion/Description&diff=21528 2014-05-08T16:39:44Z

<p>JoeriOostenrijk: </p> <hr /> <div>{{ComponentDescriptionTemplate<br /> |Reference=Hoogwijk, 2004; Van Vuuren, 2007; Hendriks et al., 2004b; Van Ruijven et al., 2007;<br /> |Description=[[TIMER model|TIMER]] includes two main energy conversion modules: Electric power generation and hydrogen generation. Below, electric power generation is described in detail. In addition, the key characteristics of the hydrogen generation model, which follows a similar structure, are presented.<br /> <br /> ==Electric power generation==<br /> As shown in the flowchart, two key elements of the electric power generation are the investment strategy and the operational strategy in the sector. A challenge in simulating electricity production in an aggregated model is that in reality electricity production depends on a range of complex factors, related to costs, reliance, and the time required to switch on technologies. Modelling these factors requires a high level of detail and thus {{AbbrTemplate|IAM}}s) such as [[TIMER model|TIMER]] concentrate on introducing a set of simplified, meta relationships ([[Hoogwijk, 2004]]; [[Van Vuuren, 2007]]).<br /> <br /> ===Total demand for new capacity===<br /> The electricity capacity required to meet the demand per region is based on a forecast of the maximum electricity demand plus a reserve margin of about 10% (including the capacity credit assigned to different forms of electricity generation). Maximum demand is calculated on the basis of an assumed monthly shape of the load duration curve (LDC) and the gross electricity demand. The latter comprises the net electricity demand from the end-use sectors plus electricity trade and transmission losses ({{AbbrTemplate|LDC}}) accounts for characteristics such as cooling and lighting demand). The demand for new generation capacity is the difference between the required and existing capacity. Power plants are assumed to be replaced at the end of their lifetime, which varies from 30 to 50 years, depending on the technology and is currently fixed in the model.<br /> <br /> ===Decisions to invest in specific options ===<br /> In the following step, a decision is made to invest in different generation technologies. In the model, this is done on the basis of the price of electricity (in USD/kWhe) produced per technology, using a multinomial logit equation that assigns larger market shares to the lower cost options. The specific costs of each option is broken down into a number of categories: investment or capital costs (USD/kWe), fuel costs (USD/GJ), operational and maintenance costs (OM) and other costs (see further). An exception is hydropower capacity, which is exogenously prescribed, because large hydropower plants often have functions other than only electricity production (e.g. water supply and flood control). In the equations, some constraints are added to account for limitations in supply (e.g. restrictions on biomass availability). The investments needed for each option are given in the form of total investment in new generation capacity and the share of each individual technology (determined on the basis of price and preference).<br /> <br /> ===Operational strategy===<br /> Use of power plants is based on operational costs, with low-cost technologies assumed to be used most often. This implies that capital-intensive plants with low operational costs, such as renewable and nuclear energy, operate as many hours as possible. To some degree, this is also true for other plants with low operational costs, such as coal. <br /> The operational decision is presented in the following three steps:<br /> #Renewable sources PV and wind are assigned, followed by hydropower, because these options have the lowest operational costs;<br /> #The peak load capacity (period of high electricity demand) is assigned on the basis of the operational costs of each available plant and the ability of these plants to provide peak load capacity; <br /> #Base load (period of medium to low energy demand) is assigned on the basis of the remaining capacity (after steps 1 and 2), operational costs and the ability of options to provide the base load capacity.<br /> <br /> <br /> ===Fossil-fuel and bio-energy power plants===<br /> A total of 20 types of power plants generating electricity using fossil fuels and bioenergy are included. These power plants represent different combinations of conventional technology, such as gasification and combined cycle (CC) technology; combined heat and power (CHP); and carbon capture and storage (CCS;([[Hendriks et al., 2004b]]). The specific capital costs and thermal efficiencies of these types of plants are determined by exogenous assumptions that describe the technological progress of typical components of these plants:<br /> *For conventional power plants, the coal-fired plant is defined in terms of overall efficiency and investment cost. The characteristics of all other conventional plants (using oil, natural gas or bioenergy) are described in the investment differences for desulphurisation, fuel handling and efficiency.<br /> *For Combined Cycle (CC) power plants, the characteristics of a natural gas fired plant are set as the standard. Other CC plants (fuelled by oil, bioenergy and coal after gasification) are defined by indicating additional capital costs for gasification, efficiency losses due to gasification, and operation and maintenance (O&amp;M) costs for fuel handling. <br /> *Power plants with carbon-capture-and-storage systems (CCS) are assumed to be CC plants, but with fuel-specific lower efficiency and higher investment and O&amp;M costs (related to capture and storage). <br /> *The characteristics of combined-heat-and-power plants (CHP) are similar to those of other plants, but with an assumed small increase in capital costs, in combination with a lower efficiency for electric conversion and an added factor for heat efficiency. <br /> <br /> The cost of one unit electricity generated is equal to the sum of the capital cost, operational and maintenance costs (O&amp;M), fuel cost, and CO2 storage cost.<br /> <br /> ===Solar and wind power===<br /> <br /> The costs of solar and wind power in the model are determined by learning and depletion dynamics. For renewable energy, costs relate to capital, O&amp;M and system integration. The capital costs mostly relate to learning and depletion processes. Learning is represented by in learning curves (see flowchart); depletion is by long-term in cost–supply curves. <br /> <br /> The additional system integration costs relate to curtailed electricity (if production exceeds demand and the overcapacity cannot be used within the system), backup capacity; and additional required spinning reserve. The last items are needed to avoid loss of power if the supply of wind or solar power drops suddenly, enabling a power scale up in a relatively short time, in power stations operating below maximum capacity ([[Hoogwijk, 2004]]).<br /> <br /> To determine curtailed electricity, the model compares 10 points on the load-demand curve at the overlap between demand and supply. For both wind and solar power, a typical load supply curve is assumed (see [[Hoogwijk, 2004]]). If supply exceeds demand, the overcapacity in electricity is assumed to be discarded, resulting in higher production costs.<br /> <br /> Because wind and solar power supply is intermittent (variable and thus not reliable), the model assumes that backup capacity needs to be installed. It is assumed that no backup is required for first 5% penetration of the intermittent capacity. However, for higher levels of penetration, the effective capacity (degree to which operators can rely on plants producing at a specific time) of intermittent resources is assumed to decrease. This is referred to as the capacity factor. This decrease leads to the need for backup power by low-cost options, such as gas turbines, the cost of which is allocated to the intermittent source.<br /> <br /> The required spinning reserve of the power system is the capacity that can be used to respond to a rapid increase in demand. This is assumed to be 3.5% of the installed capacity of a conventional power plant. If wind and solar power further penetrate the market, the model assumes an additional, required spinning reserve of 15% of the intermittent capacity (after subtraction of the 3.5% existing capacity). The related costs are allocated to the intermittent source.<br /> <br /> <br /> <br /> ==Nuclear power==<br /> The costs of nuclear power also include capital, O&amp;M and nuclear fuel costs. Similar to the renewable energy options, technology improvement in nuclear power is described via a learning curve (costs decrease with cumulative installed capacity). Fuel costs increase as a function of depletion. Fuel costs are determined on the basis of the estimated extraction costs for uranium and thorium resources, see [[Energy Supply]]. A small trade model for these fission fuels is included..<br /> <br /> ==Hydrogen generation model==<br /> The structure of the hydrogen generation submodule is similar to that for electric power generation ([[Van Ruijven et al., 2007]]) but with following differences:<br /> *There are only eleven supply options for hydrogen production coal, oil, natural gas and bioenergy, with and without carbon capture and storage (8 plants); hydrogen production from electrolysis, direct hydrogen production from solar thermal processes; and small methane reform plants. <br /> *No description of preferences for different power plants is taken into account in the operational strategy. The load factor for each option equals the total production divided by the capacity for each region.<br /> *Intermittence does not play an important role because hydrogen can be stored to some degree. Thus, there are no equations simulating system integration.<br /> *Hydrogen can be traded. A trade model is added, similar to those for fossil fuels described in [[Energy Supply]].<br /> }}</div>

JoeriOostenrijk https://models.pbl.nl/index.php?title=Energy_conversion/Description&diff=21527 2014-05-08T16:38:16Z

<p>JoeriOostenrijk: </p> <hr /> <div>{{ComponentDescriptionTemplate<br /> |Reference=Hoogwijk, 2004; Van Vuuren, 2007; Hendriks et al., 2004b; Van Ruijven et al., 2007;<br /> |Description=[[TIMER model|TIMER]] includes two main energy conversion modules: Electric power generation and hydrogen generation. Below, electric power generation is described in detail. In addition, the key characteristics of the hydrogen generation model, which follows a similar structure, are presented.<br /> <br /> ==Electric power generation==<br /> As shown in the flowchart, two key elements of the electric power generation are the investment strategy and the operational strategy in the sector. A challenge in simulating electricity production in an aggregated model is that in reality electricity production depends on a range of complex factors, related to costs, reliance, and the time required to switch on technologies. Modelling these factors requires a high level of detail and thus {{AbbrTemplate|IAM}}s) such as [[TIMER model|TIMER]] concentrate on introducing a set of simplified, meta relationships ([[Hoogwijk, 2004]]; [[Van Vuuren, 2007]]).<br /> <br /> ===Total demand for new capacity===<br /> The electricity capacity required to meet the demand per region is based on a forecast of the maximum electricity demand plus a reserve margin of about 10% (including the capacity credit assigned to different forms of electricity generation). Maximum demand is calculated on the basis of an assumed monthly shape of the load duration curve (LDC) and the gross electricity demand. The latter comprises the net electricity demand from the end-use sectors plus electricity trade and transmission losses ({{AbbrTemplate|LDC}}) accounts for characteristics such as cooling and lighting demand). The demand for new generation capacity is the difference between the required and existing capacity. Power plants are assumed to be replaced at the end of their lifetime, which varies from 30 to 50 years, depending on the technology and is currently fixed in the model.<br /> <br /> ===Decisions to invest in specific options ===<br /> In the following step, a decision is made to invest in different generation technologies. In the model, this is done on the basis of the price of electricity (in USD/kWhe) produced per technology, using a multinomial logit equation that assigns larger market shares to the lower cost options. The specific costs of each option is broken down into a number of categories: investment or capital costs (USD/kWe), fuel costs (USD/GJ), operational and maintenance costs (OM) and other costs (see further). An exception is hydropower capacity, which is exogenously prescribed, because large hydropower plants often have functions other than only electricity production (e.g. water supply and flood control). In the equations, some constraints are added to account for limitations in supply (e.g. restrictions on biomass availability). The investments needed for each option are given in the form of total investment in new generation capacity and the share of each individual technology (determined on the basis of price and preference).<br /> <br /> ===Operational strategy===<br /> Use of power plants is based on operational costs, with low-cost technologies assumed to be used most often. This implies that capital-intensive plants with low operational costs, such as renewable and nuclear energy, operate as many hours as possible. To some degree, this is also true for other plants with low operational costs, such as coal. <br /> The operational decision is presented in the following three steps:<br /> #Renewable sources PV and wind are assigned, followed by hydropower, because these options have the lowest operational costs;<br /> #The peak load capacity (period of high electricity demand) is assigned on the basis of the operational costs of each available plant and the ability of these plants to provide peak load capacity; <br /> #Base load (period of medium to low energy demand) is assigned on the basis of the remaining capacity (after steps 1 and 2), operational costs and the ability of options to provide the base load capacity.<br /> <br /> <br /> ===Fossil-fuel and bio-energy power plants===<br /> A total of 20 types of power plants generating electricity using fossil fuels and bioenergy are included. These power plants represent different combinations of conventional technology, such as gasification and combined cycle (CC) technology; combined heat and power (CHP); and carbon capture and storage ([[CCS]];([[Hendriks et al., 2004b]]). The specific capital costs and thermal efficiencies of these types of plants are determined by exogenous assumptions that describe the technological progress of typical components of these plants:<br /> *For conventional power plants, the coal-fired plant is defined in terms of overall efficiency and investment cost. The characteristics of all other conventional plants (using oil, natural gas or bioenergy) are described in the investment differences for desulphurisation, fuel handling and efficiency.<br /> *For Combined Cycle (CC) power plants, the characteristics of a natural gas fired plant are set as the standard. Other CC plants (fuelled by oil, bioenergy and coal after gasification) are defined by indicating additional capital costs for gasification, efficiency losses due to gasification, and operation and maintenance (O&amp;M) costs for fuel handling. <br /> *Power plants with carbon-capture-and-storage systems (CCS) are assumed to be CC plants, but with fuel-specific lower efficiency and higher investment and O&amp;M costs (related to capture and storage). <br /> *The characteristics of combined-heat-and-power plants (CHP) are similar to those of other plants, but with an assumed small increase in capital costs, in combination with a lower efficiency for electric conversion and an added factor for heat efficiency. <br /> <br /> The cost of one unit electricity generated is equal to the sum of the capital cost, operational and maintenance costs (O&amp;M), fuel cost, and CO2 storage cost.<br /> <br /> ===Solar and wind power===<br /> <br /> The costs of solar and wind power in the model are determined by learning and depletion dynamics. For renewable energy, costs relate to capital, O&amp;M and system integration. The capital costs mostly relate to learning and depletion processes. Learning is represented by in learning curves (Box 4.1.3.1); depletion is by long-term in cost–supply curves. <br /> <br /> The additional system integration costs relate to curtailed electricity (if production exceeds demand and the overcapacity cannot be used within the system), backup capacity; and additional required spinning reserve. The last items are needed to avoid loss of power if the supply of wind or solar power drops suddenly, enabling a power scale up in a relatively short time, in power stations operating below maximum capacity ([[Hoogwijk, 2004]]).<br /> <br /> To determine curtailed electricity, the model compares 10 points on the load-demand curve at the overlap between demand and supply. For both wind and solar power, a typical load supply curve is assumed (see [[Hoogwijk, 2004]]). If supply exceeds demand, the overcapacity in electricity is assumed to be discarded, resulting in higher production costs.<br /> <br /> Because wind and solar power supply is intermittent (variable and thus not reliable), the model assumes that backup capacity needs to be installed. It is assumed that no backup is required for first 5% penetration of the intermittent capacity. However, for higher levels of penetration, the effective capacity (degree to which operators can rely on plants producing at a specific time) of intermittent resources is assumed to decrease. This is referred to as the capacity factor. This decrease leads to the need for backup power by low-cost options, such as gas turbines, the cost of which is allocated to the intermittent source.<br /> <br /> The required spinning reserve of the power system is the capacity that can be used to respond to a rapid increase in demand. This is assumed to be 3.5% of the installed capacity of a conventional power plant. If wind and solar power further penetrate the market, the model assumes an additional, required spinning reserve of 15% of the intermittent capacity (after subtraction of the 3.5% existing capacity). The related costs are allocated to the intermittent source.<br /> <br /> {{FormulaAndTableTemplate|Formula1_ED}}<br /> <br /> ==Nuclear power==<br /> The costs of nuclear power also include capital, O&amp;M and nuclear fuel costs. Similar to the renewable energy options, technology improvement in nuclear power is described via a learning curve (costs decrease with cumulative installed capacity). Fuel costs increase as a function of depletion. Fuel costs are determined on the basis of the estimated extraction costs for uranium and thorium resources, see [[Energy Supply]]. A small trade model for these fission fuels is included..<br /> <br /> ==Hydrogen generation model==<br /> The structure of the hydrogen generation submodule is similar to that for electric power generation ([[Van Ruijven et al., 2007]]) but with following differences:<br /> *There are only eleven supply options for hydrogen production coal, oil, natural gas and bioenergy, with and without carbon capture and storage (8 plants); hydrogen production from electrolysis, direct hydrogen production from solar thermal processes; and small methane reform plants. <br /> *No description of preferences for different power plants is taken into account in the operational strategy. The load factor for each option equals the total production divided by the capacity for each region.<br /> *Intermittence does not play an important role because hydrogen can be stored to some degree. Thus, there are no equations simulating system integration.<br /> *Hydrogen can be traded. A trade model is added, similar to those for fossil fuels described in [[Energy Supply]].<br /> <br /> ===Total demand for new capacity===<br /> The electricity capacity required to meet the demand per region is based on a forecast of the maximum electricity demand plus a reserve margin of about 10% (including the capacity credit assigned to different forms of electricity generation). Maximum demand is calculated on the basis of an assumed monthly shape of the load duration curve (LDC) and the gross electricity demand. The latter comprises the net electricity demand from the end-use sectors plus electricity trade and transmission losses ({{AbbrTemplate|LDC}}) accounts for characteristics such as cooling and lighting demand). The demand for new generation capacity is the difference between the required and existing capacity. Power plants are assumed to be replaced at the end of their lifetime, which varies from 30 to 50 years, depending on the technology and is currently fixed in the model.<br /> <br /> ===Decisions to invest in specific options ===<br /> In the following step, a decision is made to invest in different generation technologies. In the model, this is done on the basis of the price of electricity (in {{AbbrTemplate|USD/kWhe}} produced per technology, using a multinomial logit equation that assigns larger market shares to the lower cost options. The specific costs of each option is broken down into a number of categories: investment or capital costs (USD/kWe), fuel costs ([[HasAcronym::USD/GJ]]), operational and maintenance costs (OM) and other costs (see further). An exception is hydropower capacity, which is exogenously prescribed, because large hydropower plants often have functions other than only electricity production (e.g. water supply and flood control). In the equations, some constraints are added to account for limitations in supply (e.g. restrictions on biomass availability). The investments needed for each option are given in the form of total investment in new generation capacity and the share of each individual technology (determined on the basis of price and preference).<br /> <br /> ===Operational strategy===<br /> Use of power plants is based on operational costs, with low-cost technologies assumed to be used most often. This implies that capital-intensive plants with low operational costs, such as renewable and nuclear energy, operate as many hours as possible. To some degree, this is also true for other plants with low operational costs, such as coal. <br /> The operational decision is presented in the following three steps:<br /> #Renewable sources PV and wind are assigned, followed by hydropower, because these options have the lowest operational costs;<br /> #The peak load capacity (period of high electricity demand) is assigned on the basis of the operational costs of each available plant and the ability of these plants to provide peak load capacity; <br /> #Base load (period of medium to low energy demand) is assigned on the basis of the remaining capacity (after steps 1 and 2), operational costs and the ability of options to provide the base load capacity.<br /> <br /> <br /> ===Fossil-fuel and bio-energy power plants===<br /> A total of 20 types of power plants generating electricity using fossil fuels and bioenergy are included. These power plants represent different combinations of conventional technology, such as gasification and combined cycle (CC) technology; combined heat and power (CHP); and carbon capture and storage ({{AbbrTemplate|CCS}};([[Hendriks et al., 2004b]]). The specific capital costs and thermal efficiencies of these types of plants are determined by exogenous assumptions that describe the technological progress of typical components of these plants:<br /> *For conventional power plants, the coal-fired plant is defined in terms of overall efficiency and investment cost. The characteristics of all other conventional plants (using oil, natural gas or bioenergy) are described in the investment differences for desulphurisation, fuel handling and efficiency.<br /> *For Combined Cycle (CC) power plants, the characteristics of a natural gas fired plant are set as the standard. Other CC plants (fuelled by oil, bioenergy and coal after gasification) are defined by indicating additional capital costs for gasification, efficiency losses due to gasification, and operation and maintenance (O&amp;M) costs for fuel handling. <br /> *Power plants with carbon-capture-and-storage systems (CCS) are assumed to be CC plants, but with fuel-specific lower efficiency and higher investment and O&amp;M costs (related to capture and storage). <br /> *The characteristics of combined-heat-and-power plants (CHP) are similar to those of other plants, but with an assumed small increase in capital costs, in combination with a lower efficiency for electric conversion and an added factor for heat efficiency. <br /> <br /> The cost of one unit electricity generated is equal to the sum of the capital cost, operational and maintenance costs (O&amp;M), fuel cost, and CO2 storage cost.<br /> <br /> ===Solar and wind power===<br /> <br /> The costs of solar and wind power in the model are determined by learning and depletion dynamics. For renewable energy, costs relate to capital, O&amp;M and system integration. The capital costs mostly relate to learning and depletion processes. Learning is represented by in learning curves (Box 4.1.3.1); depletion is by long-term in cost–supply curves. <br /> <br /> The additional system integration costs relate to curtailed electricity (if production exceeds demand and the overcapacity cannot be used within the system), backup capacity; and additional required spinning reserve. The last items are needed to avoid loss of power if the supply of wind or solar power drops suddenly, enabling a power scale up in a relatively short time, in power stations operating below maximum capacity ([[Hoogwijk, 2004]]).<br /> <br /> To determine curtailed electricity, the model compares 10 points on the load-demand curve at the overlap between demand and supply. For both wind and solar power, a typical load supply curve is assumed (see [[Hoogwijk, 2004]]). If supply exceeds demand, the overcapacity in electricity is assumed to be discarded, resulting in higher production costs.<br /> <br /> Because wind and solar power supply is intermittent (variable and thus not reliable), the model assumes that backup capacity needs to be installed. It is assumed that no backup is required for first 5% penetration of the intermittent capacity. However, for higher levels of penetration, the effective capacity (degree to which operators can rely on plants producing at a specific time) of intermittent resources is assumed to decrease. This is referred to as the capacity factor. This decrease leads to the need for backup power by low-cost options, such as gas turbines, the cost of which is allocated to the intermittent source.<br /> <br /> The required spinning reserve of the power system is the capacity that can be used to respond to a rapid increase in demand. This is assumed to be 3.5% of the installed capacity of a conventional power plant. If wind and solar power further penetrate the market, the model assumes an additional, required spinning reserve of 15% of the intermittent capacity (after subtraction of the 3.5% existing capacity). The related costs are allocated to the intermittent source.<br /> <br /> ===Nuclear power===<br /> For nuclear power, the costs also consists of capital, O&amp;M and nuclear fuel costs. Similar to the renewable energy options, technology improvement nuclear power is described via a learning curve (so costs decrease with cumulative installed capacity). At the same time, fuel costs increase as a function of depletion. Fuel costs are determined on the basis of the estimated extraction costs of uranium and thorium resources, as is described in the component [[Energy supply]]. A small trade model for these fission fuels is included.<br /> <br /> ==Hydrogen generation model==<br /> The structure of the hydrogen model is similar to that of the electric power model ([[Van Ruijven et al., 2007]]). There are, however, some important differences:<br /> *The hydrogen model distinguishes the following 11 supply options: hydrogen production plants on the basis of coal, oil, natural gas and bio-energy, with and <br /> without carbon capture and storage (8 plants), hydrogen production from electrolysis, direct hydrogen production from solar thermal processes, and, finally, small methane reform plants. <br /> *For simplification, no description of preferences for different power plants is accounted for in the operational strategy. In other words, the load factor for each option equals the total production divided by the capacity for each region.<br /> *Intermittence does not play an important role, as hydrogen can be stored to some degree. Therefore, there are no equations simulating system integration.<br /> *Hydrogen can be traded. Therefore, a trade model is added, similar to the trade models for fossil fuels, as is described in the [[Energy supply]] section.<br /> <br /> &lt;references/&gt;<br /> }}</div>

JoeriOostenrijk https://models.pbl.nl/index.php?title=Energy_conversion/Description&diff=21526 2014-05-08T16:36:53Z

<p>JoeriOostenrijk: </p> <hr /> <div>{{ComponentDescriptionTemplate<br /> |Reference=Hoogwijk, 2004; Van Vuuren, 2007; Hendriks et al., 2004b; Van Ruijven et al., 2007;<br /> |Description=[[TIMER model|TIMER]] includes two main energy conversion modules: Electric power generation and hydrogen generation. Below, electric power generation is described in detail. In addition, the key characteristics of the hydrogen generation model, which follows a similar structure, are presented.<br /> <br /> ==Electric power generation==<br /> As shown in the flowchart, two key elements of the electric power generation are the investment strategy and the operational strategy in the sector. A challenge in simulating electricity production in an aggregated model is that in reality electricity production depends on a range of complex factors, related to costs, reliance, and the time required to switch on technologies. Modelling these factors requires a high level of detail and thus {{AbbrTemplate|IAM}}s) such as [[TIMER model|TIMER]] concentrate on introducing a set of simplified, meta relationships ([[Hoogwijk, 2004]]; [[Van Vuuren, 2007]]).<br /> <br /> ===Total demand for new capacity===<br /> The electricity capacity required to meet the demand per region is based on a forecast of the maximum electricity demand plus a reserve margin of about 10% (including the capacity credit assigned to different forms of electricity generation). Maximum demand is calculated on the basis of an assumed monthly shape of the load duration curve (LDC) and the gross electricity demand. The latter comprises the net electricity demand from the end-use sectors plus electricity trade and transmission losses ({{AbbrTemplate|LDC}}) accounts for characteristics such as cooling and lighting demand). The demand for new generation capacity is the difference between the required and existing capacity. Power plants are assumed to be replaced at the end of their lifetime, which varies from 30 to 50 years, depending on the technology and is currently fixed in the model.<br /> <br /> ===Decisions to invest in specific options ===<br /> In the following step, a decision is made to invest in different generation technologies. In the model, this is done on the basis of the price of electricity (in USD/kWhe) produced per technology, using a multinomial logit equation that assigns larger market shares to the lower cost options. The specific costs of each option is broken down into a number of categories: investment or capital costs (USD/kWe), fuel costs (USD/GJ), operational and maintenance costs (OM) and other costs (see further). An exception is hydropower capacity, which is exogenously prescribed, because large hydropower plants often have functions other than only electricity production (e.g. water supply and flood control). In the equations, some constraints are added to account for limitations in supply (e.g. restrictions on biomass availability). The investments needed for each option are given in the form of total investment in new generation capacity and the share of each individual technology (determined on the basis of price and preference).<br /> <br /> ===Operational strategy===<br /> Use of power plants is based on operational costs, with low-cost technologies assumed to be used most often. This implies that capital-intensive plants with low operational costs, such as renewable and nuclear energy, operate as many hours as possible. To some degree, this is also true for other plants with low operational costs, such as coal. <br /> The operational decision is presented in the following three steps:<br /> #Renewable sources PV and wind are assigned, followed by hydropower, because these options have the lowest operational costs;<br /> #The peak load capacity (period of high electricity demand) is assigned on the basis of the operational costs of each available plant and the ability of these plants to provide peak load capacity; <br /> #Base load (period of medium to low energy demand) is assigned on the basis of the remaining capacity (after steps 1 and 2), operational costs and the ability of options to provide the base load capacity.<br /> <br /> <br /> ===Fossil-fuel and bio-energy power plants===<br /> A total of 20 types of power plants generating electricity using fossil fuels and bioenergy are included. These power plants represent different combinations of conventional technology, such as gasification and combined cycle (CC) technology; combined heat and power (CHP); and carbon capture and storage ([[CCS]];([[Hendriks et al., 2004b]]). The specific capital costs and thermal efficiencies of these types of plants are determined by exogenous assumptions that describe the technological progress of typical components of these plants:<br /> *For conventional power plants, the coal-fired plant is defined in terms of overall efficiency and investment cost. The characteristics of all other conventional plants (using oil, natural gas or bioenergy) are described in the investment differences for desulphurisation, fuel handling and efficiency.<br /> *For Combined Cycle (CC) power plants, the characteristics of a natural gas fired plant are set as the standard. Other CC plants (fuelled by oil, bioenergy and coal after gasification) are defined by indicating additional capital costs for gasification, efficiency losses due to gasification, and operation and maintenance (O&amp;M) costs for fuel handling. <br /> *Power plants with carbon-capture-and-storage systems (CCS) are assumed to be CC plants, but with fuel-specific lower efficiency and higher investment and O&amp;M costs (related to capture and storage). <br /> *The characteristics of combined-heat-and-power plants (CHP) are similar to those of other plants, but with an assumed small increase in capital costs, in combination with a lower efficiency for electric conversion and an added factor for heat efficiency. <br /> <br /> The cost of one unit electricity generated is equal to the sum of the capital cost, operational and maintenance costs (O&amp;M), fuel cost, and CO2 storage cost.<br /> <br /> ===Solar and wind power===<br /> <br /> The costs of solar and wind power in the model are determined by learning and depletion dynamics. For renewable energy, costs relate to capital, O&amp;M and system integration. The capital costs mostly relate to learning and depletion processes. Learning is represented by in learning curves (Box 4.1.3.1); depletion is by long-term in cost–supply curves. <br /> <br /> The additional system integration costs relate to curtailed electricity (if production exceeds demand and the overcapacity cannot be used within the system), backup capacity; and additional required spinning reserve. The last items are needed to avoid loss of power if the supply of wind or solar power drops suddenly, enabling a power scale up in a relatively short time, in power stations operating below maximum capacity ([[Hoogwijk, 2004]]).<br /> <br /> To determine curtailed electricity, the model compares 10 points on the load-demand curve at the overlap between demand and supply. For both wind and solar power, a typical load supply curve is assumed (see [[Hoogwijk, 2004]]). If supply exceeds demand, the overcapacity in electricity is assumed to be discarded, resulting in higher production costs.<br /> <br /> Because wind and solar power supply is intermittent (variable and thus not reliable), the model assumes that backup capacity needs to be installed. It is assumed that no backup is required for first 5% penetration of the intermittent capacity. However, for higher levels of penetration, the effective capacity (degree to which operators can rely on plants producing at a specific time) of intermittent resources is assumed to decrease. This is referred to as the capacity factor. This decrease leads to the need for backup power by low-cost options, such as gas turbines, the cost of which is allocated to the intermittent source.<br /> <br /> The required spinning reserve of the power system is the capacity that can be used to respond to a rapid increase in demand. This is assumed to be 3.5% of the installed capacity of a conventional power plant. If wind and solar power further penetrate the market, the model assumes an additional, required spinning reserve of 15% of the intermittent capacity (after subtraction of the 3.5% existing capacity). The related costs are allocated to the intermittent source.<br /> <br /> {{FormulaAndTableTemplate|Formula1_ED}}<br /> <br /> ==Nuclear power==<br /> The costs of nuclear power also include capital, O&amp;M and nuclear fuel costs. Similar to the renewable energy options, technology improvement in nuclear power is described via a learning curve (costs decrease with cumulative installed capacity). Fuel costs increase as a function of depletion. Fuel costs are determined on the basis of the estimated extraction costs for uranium and thorium resources, see [[Energy Supply]]. A small trade model for these fission fuels is included..<br /> <br /> ==Hydrogen generation model==<br /> The structure of the hydrogen generation submodule is similar to that for electric power generation ([[Van Ruijven et al., 2007]]) but with following differences:<br /> *There are only eleven supply options for hydrogen production coal, oil, natural gas and bioenergy, with and without carbon capture and storage (8 plants); hydrogen production from electrolysis, direct hydrogen production from solar thermal processes; and small methane reform plants. <br /> *No description of preferences for different power plants is taken into account in the operational strategy. The load factor for each option equals the total production divided by the capacity for each region.<br /> *Intermittence does not play an important role because hydrogen can be stored to some degree. Thus, there are no equations simulating system integration.<br /> *Hydrogen can be traded. A trade model is added, similar to those for fossil fuels described in [[Energy Supply]].<br /> <br /> ===Total demand for new capacity===<br /> The electricity capacity required to meet the demand per region is based on a forecast of the maximum electricity demand plus a reserve margin of about 10% (including the capacity credit assigned to different forms of electricity generation). Maximum demand is calculated on the basis of an assumed monthly shape of the load duration curve (LDC) and the gross electricity demand. The latter comprises the net electricity demand from the end-use sectors plus electricity trade and transmission losses ({{AbbrTemplate|LDC}}) accounts for characteristics such as cooling and lighting demand). The demand for new generation capacity is the difference between the required and existing capacity. Power plants are assumed to be replaced at the end of their lifetime, which varies from 30 to 50 years, depending on the technology and is currently fixed in the model.<br /> <br /> ===Decisions to invest in specific options ===<br /> In the following step, a decision is made to invest in different generation technologies. In the model, this is done on the basis of the price of electricity (in {{AbbrTemplate|USD/kWhe}} produced per technology, using a multinomial logit equation that assigns larger market shares to the lower cost options. The specific costs of each option is broken down into a number of categories: investment or capital costs (USD/kWe), fuel costs ([[HasAcronym::USD/GJ]]), operational and maintenance costs (OM) and other costs (see further). An exception is hydropower capacity, which is exogenously prescribed, because large hydropower plants often have functions other than only electricity production (e.g. water supply and flood control). In the equations, some constraints are added to account for limitations in supply (e.g. restrictions on biomass availability). The investments needed for each option are given in the form of total investment in new generation capacity and the share of each individual technology (determined on the basis of price and preference).<br /> <br /> ===Operational strategy===<br /> Use of power plants is based on operational costs, with low-cost technologies assumed to be used most often. This implies that capital-intensive plants with low operational costs, such as renewable and nuclear energy, operate as many hours as possible. To some degree, this is also true for other plants with low operational costs, such as coal. <br /> The operational decision is presented in the following three steps:<br /> #Renewable sources PV and wind are assigned, followed by hydropower, because these options have the lowest operational costs;<br /> #The peak load capacity (period of high electricity demand) is assigned on the basis of the operational costs of each available plant and the ability of these plants to provide peak load capacity; <br /> #Base load (period of medium to low energy demand) is assigned on the basis of the remaining capacity (after steps 1 and 2), operational costs and the ability of options to provide the base load capacity.<br /> <br /> <br /> ===Fossil-fuel and bio-energy power plants===<br /> A total of 20 types of power plants generating electricity using fossil fuels and bioenergy are included. These power plants represent different combinations of conventional technology, such as gasification and combined cycle (CC) technology; combined heat and power (CHP); and carbon capture and storage (CCS;(Hendriks et al., 2004b). The specific capital costs and thermal efficiencies of these types of plants are determined by exogenous assumptions that describe the technological progress of typical components of these plants:<br /> *For conventional power plants, the coal-fired plant is defined in terms of overall efficiency and investment cost. The characteristics of all other conventional plants (using oil, natural gas or bioenergy) are described in the investment differences for desulphurisation, fuel handling and efficiency.<br /> *For Combined Cycle (CC) power plants, the characteristics of a natural gas fired plant are set as the standard. Other CC plants (fuelled by oil, bioenergy and coal after gasification) are defined by indicating additional capital costs for gasification, efficiency losses due to gasification, and operation and maintenance (O&amp;M) costs for fuel handling. <br /> *Power plants with carbon-capture-and-storage systems (CCS) are assumed to be CC plants, but with fuel-specific lower efficiency and higher investment and O&amp;M costs (related to capture and storage). <br /> *The characteristics of combined-heat-and-power plants (CHP) are similar to those of other plants, but with an assumed small increase in capital costs, in combination with a lower efficiency for electric conversion and an added factor for heat efficiency. <br /> <br /> The cost of one unit electricity generated is equal to the sum of the capital cost, operational and maintenance costs (O&amp;M), fuel cost, and CO2 storage cost.<br /> <br /> ===Solar and wind power===<br /> <br /> The costs of solar and wind power in the model are determined by learning and depletion dynamics. For renewable energy, costs relate to capital, O&amp;M and system integration. The capital costs mostly relate to learning and depletion processes. Learning is represented by in learning curves (Box 4.1.3.1); depletion is by long-term in cost–supply curves. <br /> <br /> The additional system integration costs relate to curtailed electricity (if production exceeds demand and the overcapacity cannot be used within the system), backup capacity; and additional required spinning reserve. The last items are needed to avoid loss of power if the supply of wind or solar power drops suddenly, enabling a power scale up in a relatively short time, in power stations operating below maximum capacity ([[Hoogwijk, 2004]]).<br /> <br /> To determine curtailed electricity, the model compares 10 points on the load-demand curve at the overlap between demand and supply. For both wind and solar power, a typical load supply curve is assumed (see [[Hoogwijk, 2004]]). If supply exceeds demand, the overcapacity in electricity is assumed to be discarded, resulting in higher production costs.<br /> <br /> Because wind and solar power supply is intermittent (variable and thus not reliable), the model assumes that backup capacity needs to be installed. It is assumed that no backup is required for first 5% penetration of the intermittent capacity. However, for higher levels of penetration, the effective capacity (degree to which operators can rely on plants producing at a specific time) of intermittent resources is assumed to decrease. This is referred to as the capacity factor. This decrease leads to the need for backup power by low-cost options, such as gas turbines, the cost of which is allocated to the intermittent source.<br /> <br /> The required spinning reserve of the power system is the capacity that can be used to respond to a rapid increase in demand. This is assumed to be 3.5% of the installed capacity of a conventional power plant. If wind and solar power further penetrate the market, the model assumes an additional, required spinning reserve of 15% of the intermittent capacity (after subtraction of the 3.5% existing capacity). The related costs are allocated to the intermittent source.<br /> <br /> ==Nuclear power==<br /> For nuclear power, the costs also consists of capital, O&amp;M and nuclear fuel costs. Similar to the renewable energy options, technology improvement nuclear power is described via a learning curve (so costs decrease with cumulative installed capacity). At the same time, fuel costs increase as a function of depletion. Fuel costs are determined on the basis of the estimated extraction costs of uranium and thorium resources, as is described in the component [[Energy supply]]. A small trade model for these fission fuels is included.<br /> <br /> ==Hydrogen generation model==<br /> The structure of the hydrogen model is similar to that of the electric power model ([[Van Ruijven et al., 2007]]). There are, however, some important differences:<br /> *The hydrogen model distinguishes the following 11 supply options: hydrogen production plants on the basis of coal, oil, natural gas and bio-energy, with and <br /> without carbon capture and storage (8 plants), hydrogen production from electrolysis, direct hydrogen production from solar thermal processes, and, finally, small methane reform plants. <br /> *For simplification, no description of preferences for different power plants is accounted for in the operational strategy. In other words, the load factor for each option equals the total production divided by the capacity for each region.<br /> *Intermittence does not play an important role, as hydrogen can be stored to some degree. Therefore, there are no equations simulating system integration.<br /> *Hydrogen can be traded. Therefore, a trade model is added, similar to the trade models for fossil fuels, as is described in the [[Energy supply]] section.<br /> <br /> &lt;references/&gt;<br /> }}</div>

JoeriOostenrijk https://models.pbl.nl/index.php?title=Energy_conversion/Description&diff=21525 2014-05-08T16:36:16Z

<p>JoeriOostenrijk: </p> <hr /> <div>{{ComponentDescriptionTemplate<br /> |Reference=Hoogwijk, 2004; Van Vuuren, 2007; Hendriks et al., 2004b; Van Ruijven et al., 2007;<br /> |Description=[[TIMER model|TIMER]] includes two main energy conversion modules: Electric power generation and hydrogen generation. Below, electric power generation is described in detail. In addition, the key characteristics of the hydrogen generation model, which follows a similar structure, are presented.<br /> <br /> ==Electric power generation==<br /> As shown in the flowchart, two key elements of the electric power generation are the investment strategy and the operational strategy in the sector. A challenge in simulating electricity production in an aggregated model is that in reality electricity production depends on a range of complex factors, related to costs, reliance, and the time required to switch on technologies. Modelling these factors requires a high level of detail and thus {{AbbrTemplate|IAM}}s such as [[TIMER model|TIMER]] concentrate on introducing a set of simplified, meta relationships ([[Hoogwijk, 2004]]; [[Van Vuuren, 2007]]).<br /> <br /> ===Total demand for new capacity===<br /> The electricity capacity required to meet the demand per region is based on a forecast of the maximum electricity demand plus a reserve margin of about 10% (including the capacity credit assigned to different forms of electricity generation). Maximum demand is calculated on the basis of an assumed monthly shape of the load duration curve (LDC) and the gross electricity demand. The latter comprises the net electricity demand from the end-use sectors plus electricity trade and transmission losses ({{AbbrTemplate|LDC}}) accounts for characteristics such as cooling and lighting demand). The demand for new generation capacity is the difference between the required and existing capacity. Power plants are assumed to be replaced at the end of their lifetime, which varies from 30 to 50 years, depending on the technology and is currently fixed in the model.<br /> <br /> ===Decisions to invest in specific options ===<br /> In the following step, a decision is made to invest in different generation technologies. In the model, this is done on the basis of the price of electricity (in USD/kWhe) produced per technology, using a multinomial logit equation that assigns larger market shares to the lower cost options. The specific costs of each option is broken down into a number of categories: investment or capital costs (USD/kWe), fuel costs (USD/GJ), operational and maintenance costs (OM) and other costs (see further). An exception is hydropower capacity, which is exogenously prescribed, because large hydropower plants often have functions other than only electricity production (e.g. water supply and flood control). In the equations, some constraints are added to account for limitations in supply (e.g. restrictions on biomass availability). The investments needed for each option are given in the form of total investment in new generation capacity and the share of each individual technology (determined on the basis of price and preference).<br /> <br /> ===Operational strategy===<br /> Use of power plants is based on operational costs, with low-cost technologies assumed to be used most often. This implies that capital-intensive plants with low operational costs, such as renewable and nuclear energy, operate as many hours as possible. To some degree, this is also true for other plants with low operational costs, such as coal. <br /> The operational decision is presented in the following three steps:<br /> #Renewable sources PV and wind are assigned, followed by hydropower, because these options have the lowest operational costs;<br /> #The peak load capacity (period of high electricity demand) is assigned on the basis of the operational costs of each available plant and the ability of these plants to provide peak load capacity; <br /> #Base load (period of medium to low energy demand) is assigned on the basis of the remaining capacity (after steps 1 and 2), operational costs and the ability of options to provide the base load capacity.<br /> <br /> <br /> ===Fossil-fuel and bio-energy power plants===<br /> A total of 20 types of power plants generating electricity using fossil fuels and bioenergy are included. These power plants represent different combinations of conventional technology, such as gasification and combined cycle (CC) technology; combined heat and power (CHP); and carbon capture and storage ({{AbbrTemplate|CSS}};(Hendriks et al., 2004b). The specific capital costs and thermal efficiencies of these types of plants are determined by exogenous assumptions that describe the technological progress of typical components of these plants:<br /> *For conventional power plants, the coal-fired plant is defined in terms of overall efficiency and investment cost. The characteristics of all other conventional plants (using oil, natural gas or bioenergy) are described in the investment differences for desulphurisation, fuel handling and efficiency.<br /> *For Combined Cycle (CC) power plants, the characteristics of a natural gas fired plant are set as the standard. Other CC plants (fuelled by oil, bioenergy and coal after gasification) are defined by indicating additional capital costs for gasification, efficiency losses due to gasification, and operation and maintenance (O&amp;M) costs for fuel handling. <br /> *Power plants with carbon-capture-and-storage systems (CCS) are assumed to be CC plants, but with fuel-specific lower efficiency and higher investment and O&amp;M costs (related to capture and storage). <br /> *The characteristics of combined-heat-and-power plants (CHP) are similar to those of other plants, but with an assumed small increase in capital costs, in combination with a lower efficiency for electric conversion and an added factor for heat efficiency. <br /> <br /> The cost of one unit electricity generated is equal to the sum of the capital cost, operational and maintenance costs (O&amp;M), fuel cost, and CO2 storage cost.<br /> <br /> ===Solar and wind power===<br /> <br /> The costs of solar and wind power in the model are determined by learning and depletion dynamics. For renewable energy, costs relate to capital, O&amp;M and system integration. The capital costs mostly relate to learning and depletion processes. Learning is represented by in learning curves (see flowchart on the right); depletion is by long-term in cost–supply curves. <br /> <br /> The additional system integration costs relate to curtailed electricity (if production exceeds demand and the overcapacity cannot be used within the system), backup capacity; and additional required spinning reserve. The last items are needed to avoid loss of power if the supply of wind or solar power drops suddenly, enabling a power scale up in a relatively short time, in power stations operating below maximum capacity ([[Hoogwijk, 2004]]).<br /> <br /> To determine curtailed electricity, the model compares 10 points on the load-demand curve at the overlap between demand and supply. For both wind and solar power, a typical load supply curve is assumed (see [[Hoogwijk, 2004]]). If supply exceeds demand, the overcapacity in electricity is assumed to be discarded, resulting in higher production costs.<br /> <br /> Because wind and solar power supply is intermittent (variable and thus not reliable), the model assumes that backup capacity needs to be installed. It is assumed that no backup is required for first 5% penetration of the intermittent capacity. However, for higher levels of penetration, the effective capacity (degree to which operators can rely on plants producing at a specific time) of intermittent resources is assumed to decrease. This is referred to as the capacity factor. This decrease leads to the need for backup power by low-cost options, such as gas turbines, the cost of which is allocated to the intermittent source.<br /> <br /> The required spinning reserve of the power system is the capacity that can be used to respond to a rapid increase in demand. This is assumed to be 3.5% of the installed capacity of a conventional power plant. If wind and solar power further penetrate the market, the model assumes an additional, required spinning reserve of 15% of the intermittent capacity (after subtraction of the 3.5% existing capacity). The related costs are allocated to the intermittent source.<br /> <br /> ==Nuclear power==<br /> For nuclear power, the costs also consists of capital, O&amp;M and nuclear fuel costs. Similar to the renewable energy options, technology improvement nuclear power is described via a learning curve (so costs decrease with cumulative installed capacity). At the same time, fuel costs increase as a function of depletion. Fuel costs are determined on the basis of the estimated extraction costs of uranium and thorium resources, as is described in the component [[Energy supply]]. A small trade model for these fission fuels is included.<br /> <br /> ==Hydrogen generation model==<br /> The structure of the hydrogen model is similar to that of the electric power model ([[Van Ruijven et al., 2007]]). There are, however, some important differences:<br /> *The hydrogen model distinguishes the following 11 supply options: hydrogen production plants on the basis of coal, oil, natural gas and bio-energy, with and <br /> without carbon capture and storage (8 plants), hydrogen production from electrolysis, direct hydrogen production from solar thermal processes, and, finally, small methane reform plants. <br /> *For simplification, no description of preferences for different power plants is accounted for in the operational strategy. In other words, the load factor for each option equals the total production divided by the capacity for each region.<br /> *Intermittence does not play an important role, as hydrogen can be stored to some degree. Therefore, there are no equations simulating system integration.<br /> *Hydrogen can be traded. Therefore, a trade model is added, similar to the trade models for fossil fuels, as is described in the [[Energy supply]] section.<br /> <br /> &lt;references/&gt;<br /> }}<br /> s such as [[TIMER model|TIMER]] concentrate on introducing a set of simplified, meta relationships ([[Hoogwijk, 2004]]; [[Van Vuuren, 2007]]).<br /> <br /> ===Total demand for new capacity===<br /> The electricity capacity required to meet the demand per region is based on a forecast of the maximum electricity demand plus a reserve margin of about 10% (including the capacity credit assigned to different forms of electricity generation). Maximum demand is calculated on the basis of an assumed monthly shape of the load duration curve (LDC) and the gross electricity demand. The latter comprises the net electricity demand from the end-use sectors plus electricity trade and transmission losses ({{AbbrTemplate|LDC}}) accounts for characteristics such as cooling and lighting demand). The demand for new generation capacity is the difference between the required and existing capacity. Power plants are assumed to be replaced at the end of their lifetime, which varies from 30 to 50 years, depending on the technology and is currently fixed in the model.<br /> <br /> ===Decisions to invest in specific options ===<br /> In the following step, a decision is made to invest in different generation technologies. In the model, this is done on the basis of the price of electricity (in {{AbbrTemplate|USD/kWhe}} produced per technology, using a multinomial logit equation that assigns larger market shares to the lower cost options. The specific costs of each option is broken down into a number of categories: investment or capital costs (USD/kWe), fuel costs ([[HasAcronym::USD/GJ]]), operational and maintenance costs (OM) and other costs (see further). An exception is hydropower capacity, which is exogenously prescribed, because large hydropower plants often have functions other than only electricity production (e.g. water supply and flood control). In the equations, some constraints are added to account for limitations in supply (e.g. restrictions on biomass availability). The investments needed for each option are given in the form of total investment in new generation capacity and the share of each individual technology (determined on the basis of price and preference).<br /> <br /> ===Operational strategy===<br /> Use of power plants is based on operational costs, with low-cost technologies assumed to be used most often. This implies that capital-intensive plants with low operational costs, such as renewable and nuclear energy, operate as many hours as possible. To some degree, this is also true for other plants with low operational costs, such as coal. <br /> The operational decision is presented in the following three steps:<br /> #Renewable sources PV and wind are assigned, followed by hydropower, because these options have the lowest operational costs;<br /> #The peak load capacity (period of high electricity demand) is assigned on the basis of the operational costs of each available plant and the ability of these plants to provide peak load capacity; <br /> #Base load (period of medium to low energy demand) is assigned on the basis of the remaining capacity (after steps 1 and 2), operational costs and the ability of options to provide the base load capacity.<br /> <br /> <br /> ===Fossil-fuel and bio-energy power plants===<br /> A total of 20 types of power plants generating electricity using fossil fuels and bioenergy are included. These power plants represent different combinations of conventional technology, such as gasification and combined cycle (CC) technology; combined heat and power (CHP); and carbon capture and storage (CCS;(Hendriks et al., 2004b). The specific capital costs and thermal efficiencies of these types of plants are determined by exogenous assumptions that describe the technological progress of typical components of these plants:<br /> *For conventional power plants, the coal-fired plant is defined in terms of overall efficiency and investment cost. The characteristics of all other conventional plants (using oil, natural gas or bioenergy) are described in the investment differences for desulphurisation, fuel handling and efficiency.<br /> *For Combined Cycle (CC) power plants, the characteristics of a natural gas fired plant are set as the standard. Other CC plants (fuelled by oil, bioenergy and coal after gasification) are defined by indicating additional capital costs for gasification, efficiency losses due to gasification, and operation and maintenance (O&amp;M) costs for fuel handling. <br /> *Power plants with carbon-capture-and-storage systems (CCS) are assumed to be CC plants, but with fuel-specific lower efficiency and higher investment and O&amp;M costs (related to capture and storage). <br /> *The characteristics of combined-heat-and-power plants (CHP) are similar to those of other plants, but with an assumed small increase in capital costs, in combination with a lower efficiency for electric conversion and an added factor for heat efficiency. <br /> <br /> The cost of one unit electricity generated is equal to the sum of the capital cost, operational and maintenance costs (O&amp;M), fuel cost, and CO2 storage cost.<br /> <br /> ===Solar and wind power===<br /> <br /> The costs of solar and wind power in the model are determined by learning and depletion dynamics. For renewable energy, costs relate to capital, O&amp;M and system integration. The capital costs mostly relate to learning and depletion processes. Learning is represented by in learning curves (Box 4.1.3.1); depletion is by long-term in cost–supply curves. <br /> <br /> The additional system integration costs relate to curtailed electricity (if production exceeds demand and the overcapacity cannot be used within the system), backup capacity; and additional required spinning reserve. The last items are needed to avoid loss of power if the supply of wind or solar power drops suddenly, enabling a power scale up in a relatively short time, in power stations operating below maximum capacity ([[Hoogwijk, 2004]]).<br /> <br /> To determine curtailed electricity, the model compares 10 points on the load-demand curve at the overlap between demand and supply. For both wind and solar power, a typical load supply curve is assumed (see [[Hoogwijk, 2004]]). If supply exceeds demand, the overcapacity in electricity is assumed to be discarded, resulting in higher production costs.<br /> <br /> Because wind and solar power supply is intermittent (variable and thus not reliable), the model assumes that backup capacity needs to be installed. It is assumed that no backup is required for first 5% penetration of the intermittent capacity. However, for higher levels of penetration, the effective capacity (degree to which operators can rely on plants producing at a specific time) of intermittent resources is assumed to decrease. This is referred to as the capacity factor. This decrease leads to the need for backup power by low-cost options, such as gas turbines, the cost of which is allocated to the intermittent source.<br /> <br /> The required spinning reserve of the power system is the capacity that can be used to respond to a rapid increase in demand. This is assumed to be 3.5% of the installed capacity of a conventional power plant. If wind and solar power further penetrate the market, the model assumes an additional, required spinning reserve of 15% of the intermittent capacity (after subtraction of the 3.5% existing capacity). The related costs are allocated to the intermittent source.<br /> <br /> <br /> {{FormulaAndTableTemplate|Formula1_ED}}<br /> <br /> The costs of solar and wind power are the model determined by learning and depletion dynamics. For renewable energy, costs relate to capital, O&amp;M and system integration. The capital costs mostly relate to [[Energy conversion/Description/Technical learning|learning]] and depletion processes (learning is represented by so-called learning curves; depletion is represented by long-term cost–supply curves). <br /> <br /> The additional system integration costs relate to <br /> # Discarded electricity in cases where production exceeds demand and the overcapacity cannot be used within the system;<br /> # Back-up capacity;<br /> # Additional required spinning reserve;<br /> The two last items are needed to avoid loss of power if the supply of wind or solar power suddenly drops, enabling a power scale up in a relatively short time, in power stations operating below maximum capacity ([[Hoogwijk, 2004]]).<br /> *To determine discarded electricity, the model makes a comparison between 10 different points on the load-demand curve, at the overlap between demand and supply. For both wind and solar power, a typical load–supply curve is assumed (see [[Hoogwijk, 2004]]). If supply exceeds demand, the overcapacity in electricity is assumed to be discarded, resulting in higher production costs. <br /> *Because wind and solar power supply is intermittent (i.e. it varies and therefore is not reliable), the model assumes that so-called back-up capacity needs to be installed. For the first 5% penetration of the intermittent capacity, it is assumed that no-back is required. However, for higher levels of penetration, the effective capacity (i.e. degree to which operators can rely on plants producing at a particular moment in time) of intermittent resources is assumed to decrease (referred to as the capacity factor). This decrease leads to the need of back-up power(by low-cost options, such as gas turbines), the costs of which are allocated to the intermittent source.<br /> *The required spinning reserve of the power system (capacity that can be used to respond to a rapid increase in demand) is assumed to be 3.5% of the installed capacity of a conventional power plant. If wind and solar power further penetrate the market, the model assumes an additional, required spinning reserve of 15% of the intermittent capacity (but after first subtracting the 3.5% existing capacity). The related costs are allocated to the intermittent source.<br /> <br /> ==Nuclear power==<br /> For nuclear power, the costs also consists of capital, O&amp;M and nuclear fuel costs. Similar to the renewable energy options, technology improvement nuclear power is described via a learning curve (so costs decrease with cumulative installed capacity). At the same time, fuel costs increase as a function of depletion. Fuel costs are determined on the basis of the estimated extraction costs of uranium and thorium resources, as is described in the component [[Energy supply]]. A small trade model for these fission fuels is included.<br /> <br /> ==Hydrogen generation model==<br /> The structure of the hydrogen model is similar to that of the electric power model ([[Van Ruijven et al., 2007]]). There are, however, some important differences:<br /> *The hydrogen model distinguishes the following 11 supply options: hydrogen production plants on the basis of coal, oil, natural gas and bio-energy, with and <br /> without carbon capture and storage (8 plants), hydrogen production from electrolysis, direct hydrogen production from solar thermal processes, and, finally, small methane reform plants. <br /> *For simplification, no description of preferences for different power plants is accounted for in the operational strategy. In other words, the load factor for each option equals the total production divided by the capacity for each region.<br /> *Intermittence does not play an important role, as hydrogen can be stored to some degree. Therefore, there are no equations simulating system integration.<br /> *Hydrogen can be traded. Therefore, a trade model is added, similar to the trade models for fossil fuels, as is described in the [[Energy supply]] section.<br /> <br /> &lt;references/&gt;<br /> }}</div>

JoeriOostenrijk https://models.pbl.nl/index.php?title=Energy_conversion/Description&diff=21524 2014-05-08T16:33:27Z

<p>JoeriOostenrijk: </p> <hr /> <div>{{ComponentDescriptionTemplate<br /> |Reference=Hoogwijk, 2004; Van Vuuren, 2007; Hendriks et al., 2004b; Van Ruijven et al., 2007;<br /> |Description=[[TIMER model|TIMER]] includes two main energy conversion modules: Electric power generation and hydrogen generation. Below, electric power generation is described in detail. In addition, the key characteristics of the hydrogen generation model, which follows a similar structure, are presented.<br /> <br /> ==Electric power generation==<br /> As shown in the flowchart, two key elements of the electric power generation are the investment strategy and the operational strategy in the sector. A challenge in simulating electricity production in an aggregated model is that in reality electricity production depends on a range of complex factors, related to costs, reliance, and the time required to switch on technologies. Modelling these factors requires a high level of detail and thus {{AbbrTemplate|IAM}}s such as [[TIMER model|TIMER]] concentrate on introducing a set of simplified, meta relationships ([[Hoogwijk, 2004]]; [[Van Vuuren, 2007]]).<br /> <br /> ===Total demand for new capacity===<br /> The electricity capacity required to meet the demand per region is based on a forecast of the maximum electricity demand plus a reserve margin of about 10% (including the capacity credit assigned to different forms of electricity generation). Maximum demand is calculated on the basis of an assumed monthly shape of the load duration curve (LDC) and the gross electricity demand. The latter comprises the net electricity demand from the end-use sectors plus electricity trade and transmission losses ({{AbbrTemplate|LDC}}) accounts for characteristics such as cooling and lighting demand). The demand for new generation capacity is the difference between the required and existing capacity. Power plants are assumed to be replaced at the end of their lifetime, which varies from 30 to 50 years, depending on the technology and is currently fixed in the model.<br /> <br /> ===Decisions to invest in specific options ===<br /> In the following step, a decision is made to invest in different generation technologies. In the model, this is done on the basis of the price of electricity (in USD/kWhe) produced per technology, using a multinomial logit equation that assigns larger market shares to the lower cost options. The specific costs of each option is broken down into a number of categories: investment or capital costs (USD/kWe), fuel costs (USD/GJ), operational and maintenance costs (OM) and other costs (see further). An exception is hydropower capacity, which is exogenously prescribed, because large hydropower plants often have functions other than only electricity production (e.g. water supply and flood control). In the equations, some constraints are added to account for limitations in supply (e.g. restrictions on biomass availability). The investments needed for each option are given in the form of total investment in new generation capacity and the share of each individual technology (determined on the basis of price and preference).<br /> <br /> ===Operational strategy===<br /> Use of power plants is based on operational costs, with low-cost technologies assumed to be used most often. This implies that capital-intensive plants with low operational costs, such as renewable and nuclear energy, operate as many hours as possible. To some degree, this is also true for other plants with low operational costs, such as coal. <br /> The operational decision is presented in the following three steps:<br /> #Renewable sources PV and wind are assigned, followed by hydropower, because these options have the lowest operational costs;<br /> #The peak load capacity (period of high electricity demand) is assigned on the basis of the operational costs of each available plant and the ability of these plants to provide peak load capacity; <br /> #Base load (period of medium to low energy demand) is assigned on the basis of the remaining capacity (after steps 1 and 2), operational costs and the ability of options to provide the base load capacity.<br /> <br /> <br /> ===Fossil-fuel and bio-energy power plants===<br /> A total of 20 types of power plants generating electricity using fossil fuels and bioenergy are included. These power plants represent different combinations of conventional technology, such as gasification and combined cycle (CC) technology; combined heat and power (CHP); and carbon capture and storage ({{AbbrTemplate|CSS}};(Hendriks et al., 2004b). The specific capital costs and thermal efficiencies of these types of plants are determined by exogenous assumptions that describe the technological progress of typical components of these plants:<br /> *For conventional power plants, the coal-fired plant is defined in terms of overall efficiency and investment cost. The characteristics of all other conventional plants (using oil, natural gas or bioenergy) are described in the investment differences for desulphurisation, fuel handling and efficiency.<br /> *For Combined Cycle (CC) power plants, the characteristics of a natural gas fired plant are set as the standard. Other CC plants (fuelled by oil, bioenergy and coal after gasification) are defined by indicating additional capital costs for gasification, efficiency losses due to gasification, and operation and maintenance (O&amp;M) costs for fuel handling. <br /> *Power plants with carbon-capture-and-storage systems (CCS) are assumed to be CC plants, but with fuel-specific lower efficiency and higher investment and O&amp;M costs (related to capture and storage). <br /> *The characteristics of combined-heat-and-power plants (CHP) are similar to those of other plants, but with an assumed small increase in capital costs, in combination with a lower efficiency for electric conversion and an added factor for heat efficiency. <br /> <br /> The cost of one unit electricity generated is equal to the sum of the capital cost, operational and maintenance costs (O&amp;M), fuel cost, and CO2 storage cost.<br /> <br /> ===Solar and wind power===<br /> <br /> The costs of solar and wind power in the model are determined by learning and depletion dynamics. For renewable energy, costs relate to capital, O&amp;M and system integration. The capital costs mostly relate to learning and depletion processes. Learning is represented by in learning curves (Box 4.1.3.1); depletion is by long-term in cost–supply curves. <br /> <br /> The additional system integration costs relate to curtailed electricity (if production exceeds demand and the overcapacity cannot be used within the system), backup capacity; and additional required spinning reserve. The last items are needed to avoid loss of power if the supply of wind or solar power drops suddenly, enabling a power scale up in a relatively short time, in power stations operating below maximum capacity ([[Hoogwijk, 2004]]).<br /> <br /> To determine curtailed electricity, the model compares 10 points on the load-demand curve at the overlap between demand and supply. For both wind and solar power, a typical load supply curve is assumed (see [[Hoogwijk, 2004]]). If supply exceeds demand, the overcapacity in electricity is assumed to be discarded, resulting in higher production costs.<br /> <br /> Because wind and solar power supply is intermittent (variable and thus not reliable), the model assumes that backup capacity needs to be installed. It is assumed that no backup is required for first 5% penetration of the intermittent capacity. However, for higher levels of penetration, the effective capacity (degree to which operators can rely on plants producing at a specific time) of intermittent resources is assumed to decrease. This is referred to as the capacity factor. This decrease leads to the need for backup power by low-cost options, such as gas turbines, the cost of which is allocated to the intermittent source.<br /> <br /> The required spinning reserve of the power system is the capacity that can be used to respond to a rapid increase in demand. This is assumed to be 3.5% of the installed capacity of a conventional power plant. If wind and solar power further penetrate the market, the model assumes an additional, required spinning reserve of 15% of the intermittent capacity (after subtraction of the 3.5% existing capacity). The related costs are allocated to the intermittent source.<br /> <br /> <br /> {{FormulaAndTableTemplate|Formula1_ED}}<br /> <br /> The costs of solar and wind power are the model determined by learning and depletion dynamics. For renewable energy, costs relate to capital, O&amp;M and system integration. The capital costs mostly relate to [[Energy conversion/Description/Technical learning|learning]] and depletion processes (learning is represented by so-called learning curves; depletion is represented by long-term cost–supply curves). <br /> <br /> The additional system integration costs relate to <br /> # Discarded electricity in cases where production exceeds demand and the overcapacity cannot be used within the system;<br /> # Back-up capacity;<br /> # Additional required spinning reserve;<br /> The two last items are needed to avoid loss of power if the supply of wind or solar power suddenly drops, enabling a power scale up in a relatively short time, in power stations operating below maximum capacity ([[Hoogwijk, 2004]]).<br /> *To determine discarded electricity, the model makes a comparison between 10 different points on the load-demand curve, at the overlap between demand and supply. For both wind and solar power, a typical load–supply curve is assumed (see [[Hoogwijk, 2004]]). If supply exceeds demand, the overcapacity in electricity is assumed to be discarded, resulting in higher production costs. <br /> *Because wind and solar power supply is intermittent (i.e. it varies and therefore is not reliable), the model assumes that so-called back-up capacity needs to be installed. For the first 5% penetration of the intermittent capacity, it is assumed that no-back is required. However, for higher levels of penetration, the effective capacity (i.e. degree to which operators can rely on plants producing at a particular moment in time) of intermittent resources is assumed to decrease (referred to as the capacity factor). This decrease leads to the need of back-up power(by low-cost options, such as gas turbines), the costs of which are allocated to the intermittent source.<br /> *The required spinning reserve of the power system (capacity that can be used to respond to a rapid increase in demand) is assumed to be 3.5% of the installed capacity of a conventional power plant. If wind and solar power further penetrate the market, the model assumes an additional, required spinning reserve of 15% of the intermittent capacity (but after first subtracting the 3.5% existing capacity). The related costs are allocated to the intermittent source.<br /> <br /> ==Nuclear power==<br /> For nuclear power, the costs also consists of capital, O&amp;M and nuclear fuel costs. Similar to the renewable energy options, technology improvement nuclear power is described via a learning curve (so costs decrease with cumulative installed capacity). At the same time, fuel costs increase as a function of depletion. Fuel costs are determined on the basis of the estimated extraction costs of uranium and thorium resources, as is described in the component [[Energy supply]]. A small trade model for these fission fuels is included.<br /> <br /> ==Hydrogen generation model==<br /> The structure of the hydrogen model is similar to that of the electric power model ([[Van Ruijven et al., 2007]]). There are, however, some important differences:<br /> *The hydrogen model distinguishes the following 11 supply options: hydrogen production plants on the basis of coal, oil, natural gas and bio-energy, with and <br /> without carbon capture and storage (8 plants), hydrogen production from electrolysis, direct hydrogen production from solar thermal processes, and, finally, small methane reform plants. <br /> *For simplification, no description of preferences for different power plants is accounted for in the operational strategy. In other words, the load factor for each option equals the total production divided by the capacity for each region.<br /> *Intermittence does not play an important role, as hydrogen can be stored to some degree. Therefore, there are no equations simulating system integration.<br /> *Hydrogen can be traded. Therefore, a trade model is added, similar to the trade models for fossil fuels, as is described in the [[Energy supply]] section.<br /> <br /> &lt;references/&gt;<br /> }}<br /> s such as [[TIMER model|TIMER]] concentrate on introducing a set of simplified, meta relationships ([[Hoogwijk, 2004]]; [[Van Vuuren, 2007]]).<br /> <br /> ===Total demand for new capacity===<br /> The electricity capacity required to meet the demand per region is based on a forecast of the maximum electricity demand plus a reserve margin of about 10% (including the capacity credit assigned to different forms of electricity generation). Maximum demand is calculated on the basis of an assumed monthly shape of the load duration curve (LDC) and the gross electricity demand. The latter comprises the net electricity demand from the end-use sectors plus electricity trade and transmission losses ({{AbbrTemplate|LDC}}) accounts for characteristics such as cooling and lighting demand). The demand for new generation capacity is the difference between the required and existing capacity. Power plants are assumed to be replaced at the end of their lifetime, which varies from 30 to 50 years, depending on the technology and is currently fixed in the model.<br /> <br /> ===Decisions to invest in specific options ===<br /> In the following step, a decision is made to invest in different generation technologies. In the model, this is done on the basis of the price of electricity (in {{AbbrTemplate|USD/kWhe}} produced per technology, using a multinomial logit equation that assigns larger market shares to the lower cost options. The specific costs of each option is broken down into a number of categories: investment or capital costs (USD/kWe), fuel costs ([[HasAcronym::USD/GJ]]), operational and maintenance costs (OM) and other costs (see further). An exception is hydropower capacity, which is exogenously prescribed, because large hydropower plants often have functions other than only electricity production (e.g. water supply and flood control). In the equations, some constraints are added to account for limitations in supply (e.g. restrictions on biomass availability). The investments needed for each option are given in the form of total investment in new generation capacity and the share of each individual technology (determined on the basis of price and preference).<br /> <br /> ===Operational strategy===<br /> Use of power plants is based on operational costs, with low-cost technologies assumed to be used most often. This implies that capital-intensive plants with low operational costs, such as renewable and nuclear energy, operate as many hours as possible. To some degree, this is also true for other plants with low operational costs, such as coal. <br /> The operational decision is presented in the following three steps:<br /> #Renewable sources PV and wind are assigned, followed by hydropower, because these options have the lowest operational costs;<br /> #The peak load capacity (period of high electricity demand) is assigned on the basis of the operational costs of each available plant and the ability of these plants to provide peak load capacity; <br /> #Base load (period of medium to low energy demand) is assigned on the basis of the remaining capacity (after steps 1 and 2), operational costs and the ability of options to provide the base load capacity.<br /> <br /> <br /> ===Fossil-fuel and bio-energy power plants===<br /> A total of 20 types of power plants generating electricity using fossil fuels and bioenergy are included. These power plants represent different combinations of conventional technology, such as gasification and combined cycle (CC) technology; combined heat and power (CHP); and carbon capture and storage (CCS;(Hendriks et al., 2004b). The specific capital costs and thermal efficiencies of these types of plants are determined by exogenous assumptions that describe the technological progress of typical components of these plants:<br /> *For conventional power plants, the coal-fired plant is defined in terms of overall efficiency and investment cost. The characteristics of all other conventional plants (using oil, natural gas or bioenergy) are described in the investment differences for desulphurisation, fuel handling and efficiency.<br /> *For Combined Cycle (CC) power plants, the characteristics of a natural gas fired plant are set as the standard. Other CC plants (fuelled by oil, bioenergy and coal after gasification) are defined by indicating additional capital costs for gasification, efficiency losses due to gasification, and operation and maintenance (O&amp;M) costs for fuel handling. <br /> *Power plants with carbon-capture-and-storage systems (CCS) are assumed to be CC plants, but with fuel-specific lower efficiency and higher investment and O&amp;M costs (related to capture and storage). <br /> *The characteristics of combined-heat-and-power plants (CHP) are similar to those of other plants, but with an assumed small increase in capital costs, in combination with a lower efficiency for electric conversion and an added factor for heat efficiency. <br /> <br /> The cost of one unit electricity generated is equal to the sum of the capital cost, operational and maintenance costs (O&amp;M), fuel cost, and CO2 storage cost.<br /> <br /> ===Solar and wind power===<br /> <br /> The costs of solar and wind power in the model are determined by learning and depletion dynamics. For renewable energy, costs relate to capital, O&amp;M and system integration. The capital costs mostly relate to learning and depletion processes. Learning is represented by in learning curves (Box 4.1.3.1); depletion is by long-term in cost–supply curves. <br /> <br /> The additional system integration costs relate to curtailed electricity (if production exceeds demand and the overcapacity cannot be used within the system), backup capacity; and additional required spinning reserve. The last items are needed to avoid loss of power if the supply of wind or solar power drops suddenly, enabling a power scale up in a relatively short time, in power stations operating below maximum capacity ([[Hoogwijk, 2004]]).<br /> <br /> To determine curtailed electricity, the model compares 10 points on the load-demand curve at the overlap between demand and supply. For both wind and solar power, a typical load supply curve is assumed (see [[Hoogwijk, 2004]]). If supply exceeds demand, the overcapacity in electricity is assumed to be discarded, resulting in higher production costs.<br /> <br /> Because wind and solar power supply is intermittent (variable and thus not reliable), the model assumes that backup capacity needs to be installed. It is assumed that no backup is required for first 5% penetration of the intermittent capacity. However, for higher levels of penetration, the effective capacity (degree to which operators can rely on plants producing at a specific time) of intermittent resources is assumed to decrease. This is referred to as the capacity factor. This decrease leads to the need for backup power by low-cost options, such as gas turbines, the cost of which is allocated to the intermittent source.<br /> <br /> The required spinning reserve of the power system is the capacity that can be used to respond to a rapid increase in demand. This is assumed to be 3.5% of the installed capacity of a conventional power plant. If wind and solar power further penetrate the market, the model assumes an additional, required spinning reserve of 15% of the intermittent capacity (after subtraction of the 3.5% existing capacity). The related costs are allocated to the intermittent source.<br /> <br /> <br /> {{FormulaAndTableTemplate|Formula1_ED}}<br /> <br /> The costs of solar and wind power are the model determined by learning and depletion dynamics. For renewable energy, costs relate to capital, O&amp;M and system integration. The capital costs mostly relate to [[Energy conversion/Description/Technical learning|learning]] and depletion processes (learning is represented by so-called learning curves; depletion is represented by long-term cost–supply curves). <br /> <br /> The additional system integration costs relate to <br /> # Discarded electricity in cases where production exceeds demand and the overcapacity cannot be used within the system;<br /> # Back-up capacity;<br /> # Additional required spinning reserve;<br /> The two last items are needed to avoid loss of power if the supply of wind or solar power suddenly drops, enabling a power scale up in a relatively short time, in power stations operating below maximum capacity ([[Hoogwijk, 2004]]).<br /> *To determine discarded electricity, the model makes a comparison between 10 different points on the load-demand curve, at the overlap between demand and supply. For both wind and solar power, a typical load–supply curve is assumed (see [[Hoogwijk, 2004]]). If supply exceeds demand, the overcapacity in electricity is assumed to be discarded, resulting in higher production costs. <br /> *Because wind and solar power supply is intermittent (i.e. it varies and therefore is not reliable), the model assumes that so-called back-up capacity needs to be installed. For the first 5% penetration of the intermittent capacity, it is assumed that no-back is required. However, for higher levels of penetration, the effective capacity (i.e. degree to which operators can rely on plants producing at a particular moment in time) of intermittent resources is assumed to decrease (referred to as the capacity factor). This decrease leads to the need of back-up power(by low-cost options, such as gas turbines), the costs of which are allocated to the intermittent source.<br /> *The required spinning reserve of the power system (capacity that can be used to respond to a rapid increase in demand) is assumed to be 3.5% of the installed capacity of a conventional power plant. If wind and solar power further penetrate the market, the model assumes an additional, required spinning reserve of 15% of the intermittent capacity (but after first subtracting the 3.5% existing capacity). The related costs are allocated to the intermittent source.<br /> <br /> ==Nuclear power==<br /> For nuclear power, the costs also consists of capital, O&amp;M and nuclear fuel costs. Similar to the renewable energy options, technology improvement nuclear power is described via a learning curve (so costs decrease with cumulative installed capacity). At the same time, fuel costs increase as a function of depletion. Fuel costs are determined on the basis of the estimated extraction costs of uranium and thorium resources, as is described in the component [[Energy supply]]. A small trade model for these fission fuels is included.<br /> <br /> ==Hydrogen generation model==<br /> The structure of the hydrogen model is similar to that of the electric power model ([[Van Ruijven et al., 2007]]). There are, however, some important differences:<br /> *The hydrogen model distinguishes the following 11 supply options: hydrogen production plants on the basis of coal, oil, natural gas and bio-energy, with and <br /> without carbon capture and storage (8 plants), hydrogen production from electrolysis, direct hydrogen production from solar thermal processes, and, finally, small methane reform plants. <br /> *For simplification, no description of preferences for different power plants is accounted for in the operational strategy. In other words, the load factor for each option equals the total production divided by the capacity for each region.<br /> *Intermittence does not play an important role, as hydrogen can be stored to some degree. Therefore, there are no equations simulating system integration.<br /> *Hydrogen can be traded. Therefore, a trade model is added, similar to the trade models for fossil fuels, as is described in the [[Energy supply]] section.<br /> <br /> &lt;references/&gt;<br /> }}</div>

JoeriOostenrijk https://models.pbl.nl/index.php?title=Energy_conversion/Description&diff=21523 2014-05-08T16:32:08Z

<p>JoeriOostenrijk: </p> <hr /> <div>{{ComponentDescriptionTemplate<br /> |Reference=Hoogwijk, 2004; Van Vuuren, 2007; Hendriks et al., 2004b; Van Ruijven et al., 2007;<br /> |Description=[[TIMER model|TIMER]] includes two main energy conversion modules: Electric power generation and hydrogen generation. Below, electric power generation is described in detail. In addition, the key characteristics of the hydrogen generation model, which follows a similar structure, are presented.<br /> <br /> ==Electric power generation==<br /> As shown in the flowchart, two key elements of the electric power generation are the investment strategy and the operational strategy in the sector. A challenge in simulating electricity production in an aggregated model is that in reality electricity production depends on a range of complex factors, related to costs, reliance, and the time required to switch on technologies. Modelling these factors requires a high level of detail and thus {{AbbrTemplate|IAM}}s) such as [[TIMER model|TIMER]] concentrate on introducing a set of simplified, meta relationships ([[Hoogwijk, 2004]]; [[Van Vuuren, 2007]]).<br /> <br /> ===Total demand for new capacity===<br /> The electricity capacity required to meet the demand per region is based on a forecast of the maximum electricity demand plus a reserve margin of about 10% (including the capacity credit assigned to different forms of electricity generation). Maximum demand is calculated on the basis of an assumed monthly shape of the load duration curve (LDC) and the gross electricity demand. The latter comprises the net electricity demand from the end-use sectors plus electricity trade and transmission losses ({{AbbrTemplate|LDC}}) accounts for characteristics such as cooling and lighting demand). The demand for new generation capacity is the difference between the required and existing capacity. Power plants are assumed to be replaced at the end of their lifetime, which varies from 30 to 50 years, depending on the technology and is currently fixed in the model.<br /> <br /> ===Decisions to invest in specific options ===<br /> In the following step, a decision is made to invest in different generation technologies. In the model, this is done on the basis of the price of electricity (in USD/kWhe) produced per technology, using a multinomial logit equation that assigns larger market shares to the lower cost options. The specific costs of each option is broken down into a number of categories: investment or capital costs (USD/kWe), fuel costs (USD/GJ), operational and maintenance costs (OM) and other costs (see further). An exception is hydropower capacity, which is exogenously prescribed, because large hydropower plants often have functions other than only electricity production (e.g. water supply and flood control). In the equations, some constraints are added to account for limitations in supply (e.g. restrictions on biomass availability). The investments needed for each option are given in the form of total investment in new generation capacity and the share of each individual technology (determined on the basis of price and preference).<br /> <br /> ===Operational strategy===<br /> Use of power plants is based on operational costs, with low-cost technologies assumed to be used most often. This implies that capital-intensive plants with low operational costs, such as renewable and nuclear energy, operate as many hours as possible. To some degree, this is also true for other plants with low operational costs, such as coal. <br /> The operational decision is presented in the following three steps:<br /> #Renewable sources PV and wind are assigned, followed by hydropower, because these options have the lowest operational costs;<br /> #The peak load capacity (period of high electricity demand) is assigned on the basis of the operational costs of each available plant and the ability of these plants to provide peak load capacity; <br /> #Base load (period of medium to low energy demand) is assigned on the basis of the remaining capacity (after steps 1 and 2), operational costs and the ability of options to provide the base load capacity.<br /> <br /> <br /> ===Fossil-fuel and bio-energy power plants===<br /> A total of 20 types of power plants generating electricity using fossil fuels and bioenergy are included. These power plants represent different combinations of conventional technology, such as gasification and combined cycle (CC) technology; combined heat and power (CHP); and carbon capture and storage ([[CCS]];([[Hendriks et al., 2004b]]). The specific capital costs and thermal efficiencies of these types of plants are determined by exogenous assumptions that describe the technological progress of typical components of these plants:<br /> *For conventional power plants, the coal-fired plant is defined in terms of overall efficiency and investment cost. The characteristics of all other conventional plants (using oil, natural gas or bioenergy) are described in the investment differences for desulphurisation, fuel handling and efficiency.<br /> *For Combined Cycle (CC) power plants, the characteristics of a natural gas fired plant are set as the standard. Other CC plants (fuelled by oil, bioenergy and coal after gasification) are defined by indicating additional capital costs for gasification, efficiency losses due to gasification, and operation and maintenance (O&amp;M) costs for fuel handling. <br /> *Power plants with carbon-capture-and-storage systems (CCS) are assumed to be CC plants, but with fuel-specific lower efficiency and higher investment and O&amp;M costs (related to capture and storage). <br /> *The characteristics of combined-heat-and-power plants (CHP) are similar to those of other plants, but with an assumed small increase in capital costs, in combination with a lower efficiency for electric conversion and an added factor for heat efficiency. <br /> <br /> The cost of one unit electricity generated is equal to the sum of the capital cost, operational and maintenance costs (O&amp;M), fuel cost, and CO2 storage cost.<br /> <br /> ===Solar and wind power===<br /> <br /> The costs of solar and wind power in the model are determined by learning and depletion dynamics. For renewable energy, costs relate to capital, O&amp;M and system integration. The capital costs mostly relate to learning and depletion processes. Learning is represented by in learning curves (Box 4.1.3.1); depletion is by long-term in cost–supply curves. <br /> <br /> The additional system integration costs relate to curtailed electricity (if production exceeds demand and the overcapacity cannot be used within the system), backup capacity; and additional required spinning reserve. The last items are needed to avoid loss of power if the supply of wind or solar power drops suddenly, enabling a power scale up in a relatively short time, in power stations operating below maximum capacity ([[Hoogwijk, 2004]]).<br /> <br /> To determine curtailed electricity, the model compares 10 points on the load-demand curve at the overlap between demand and supply. For both wind and solar power, a typical load supply curve is assumed (see [[Hoogwijk, 2004]]). If supply exceeds demand, the overcapacity in electricity is assumed to be discarded, resulting in higher production costs.<br /> <br /> Because wind and solar power supply is intermittent (variable and thus not reliable), the model assumes that backup capacity needs to be installed. It is assumed that no backup is required for first 5% penetration of the intermittent capacity. However, for higher levels of penetration, the effective capacity (degree to which operators can rely on plants producing at a specific time) of intermittent resources is assumed to decrease. This is referred to as the capacity factor. This decrease leads to the need for backup power by low-cost options, such as gas turbines, the cost of which is allocated to the intermittent source.<br /> <br /> The required spinning reserve of the power system is the capacity that can be used to respond to a rapid increase in demand. This is assumed to be 3.5% of the installed capacity of a conventional power plant. If wind and solar power further penetrate the market, the model assumes an additional, required spinning reserve of 15% of the intermittent capacity (after subtraction of the 3.5% existing capacity). The related costs are allocated to the intermittent source.<br /> <br /> {{FormulaAndTableTemplate|Formula1_ED}}<br /> <br /> ==Nuclear power==<br /> The costs of nuclear power also include capital, O&amp;M and nuclear fuel costs. Similar to the renewable energy options, technology improvement in nuclear power is described via a learning curve (costs decrease with cumulative installed capacity). Fuel costs increase as a function of depletion. Fuel costs are determined on the basis of the estimated extraction costs for uranium and thorium resources, see [[Energy Supply]]. A small trade model for these fission fuels is included..<br /> <br /> ==Hydrogen generation model==<br /> The structure of the hydrogen generation submodule is similar to that for electric power generation ([[Van Ruijven et al., 2007]]) but with following differences:<br /> *There are only eleven supply options for hydrogen production coal, oil, natural gas and bioenergy, with and without carbon capture and storage (8 plants); hydrogen production from electrolysis, direct hydrogen production from solar thermal processes; and small methane reform plants. <br /> *No description of preferences for different power plants is taken into account in the operational strategy. The load factor for each option equals the total production divided by the capacity for each region.<br /> *Intermittence does not play an important role because hydrogen can be stored to some degree. Thus, there are no equations simulating system integration.<br /> *Hydrogen can be traded. A trade model is added, similar to those for fossil fuels described in [[Energy Supply]].<br /> <br /> ===Total demand for new capacity===<br /> The electricity capacity required to meet the demand per region is based on a forecast of the maximum electricity demand plus a reserve margin of about 10% (including the capacity credit assigned to different forms of electricity generation). Maximum demand is calculated on the basis of an assumed monthly shape of the load duration curve (LDC) and the gross electricity demand. The latter comprises the net electricity demand from the end-use sectors plus electricity trade and transmission losses ({{AbbrTemplate|LDC}}) accounts for characteristics such as cooling and lighting demand). The demand for new generation capacity is the difference between the required and existing capacity. Power plants are assumed to be replaced at the end of their lifetime, which varies from 30 to 50 years, depending on the technology and is currently fixed in the model.<br /> <br /> ===Decisions to invest in specific options ===<br /> In the following step, a decision is made to invest in different generation technologies. In the model, this is done on the basis of the price of electricity (in {{AbbrTemplate|USD/kWhe}} produced per technology, using a multinomial logit equation that assigns larger market shares to the lower cost options. The specific costs of each option is broken down into a number of categories: investment or capital costs (USD/kWe), fuel costs ([[HasAcronym::USD/GJ]]), operational and maintenance costs (OM) and other costs (see further). An exception is hydropower capacity, which is exogenously prescribed, because large hydropower plants often have functions other than only electricity production (e.g. water supply and flood control). In the equations, some constraints are added to account for limitations in supply (e.g. restrictions on biomass availability). The investments needed for each option are given in the form of total investment in new generation capacity and the share of each individual technology (determined on the basis of price and preference).<br /> <br /> ===Operational strategy===<br /> Use of power plants is based on operational costs, with low-cost technologies assumed to be used most often. This implies that capital-intensive plants with low operational costs, such as renewable and nuclear energy, operate as many hours as possible. To some degree, this is also true for other plants with low operational costs, such as coal. <br /> The operational decision is presented in the following three steps:<br /> #Renewable sources PV and wind are assigned, followed by hydropower, because these options have the lowest operational costs;<br /> #The peak load capacity (period of high electricity demand) is assigned on the basis of the operational costs of each available plant and the ability of these plants to provide peak load capacity; <br /> #Base load (period of medium to low energy demand) is assigned on the basis of the remaining capacity (after steps 1 and 2), operational costs and the ability of options to provide the base load capacity.<br /> <br /> <br /> ===Fossil-fuel and bio-energy power plants===<br /> A total of 20 types of power plants generating electricity using fossil fuels and bioenergy are included. These power plants represent different combinations of conventional technology, such as gasification and combined cycle (CC) technology; combined heat and power (CHP); and carbon capture and storage (CCS;(Hendriks et al., 2004b). The specific capital costs and thermal efficiencies of these types of plants are determined by exogenous assumptions that describe the technological progress of typical components of these plants:<br /> *For conventional power plants, the coal-fired plant is defined in terms of overall efficiency and investment cost. The characteristics of all other conventional plants (using oil, natural gas or bioenergy) are described in the investment differences for desulphurisation, fuel handling and efficiency.<br /> *For Combined Cycle (CC) power plants, the characteristics of a natural gas fired plant are set as the standard. Other CC plants (fuelled by oil, bioenergy and coal after gasification) are defined by indicating additional capital costs for gasification, efficiency losses due to gasification, and operation and maintenance (O&amp;M) costs for fuel handling. <br /> *Power plants with carbon-capture-and-storage systems (CCS) are assumed to be CC plants, but with fuel-specific lower efficiency and higher investment and O&amp;M costs (related to capture and storage). <br /> *The characteristics of combined-heat-and-power plants (CHP) are similar to those of other plants, but with an assumed small increase in capital costs, in combination with a lower efficiency for electric conversion and an added factor for heat efficiency. <br /> <br /> The cost of one unit electricity generated is equal to the sum of the capital cost, operational and maintenance costs (O&amp;M), fuel cost, and CO2 storage cost.<br /> <br /> ===Solar and wind power===<br /> <br /> The costs of solar and wind power in the model are determined by learning and depletion dynamics. For renewable energy, costs relate to capital, O&amp;M and system integration. The capital costs mostly relate to learning and depletion processes. Learning is represented by in learning curves (Box 4.1.3.1); depletion is by long-term in cost–supply curves. <br /> <br /> The additional system integration costs relate to curtailed electricity (if production exceeds demand and the overcapacity cannot be used within the system), backup capacity; and additional required spinning reserve. The last items are needed to avoid loss of power if the supply of wind or solar power drops suddenly, enabling a power scale up in a relatively short time, in power stations operating below maximum capacity ([[Hoogwijk, 2004]]).<br /> <br /> To determine curtailed electricity, the model compares 10 points on the load-demand curve at the overlap between demand and supply. For both wind and solar power, a typical load supply curve is assumed (see [[Hoogwijk, 2004]]). If supply exceeds demand, the overcapacity in electricity is assumed to be discarded, resulting in higher production costs.<br /> <br /> Because wind and solar power supply is intermittent (variable and thus not reliable), the model assumes that backup capacity needs to be installed. It is assumed that no backup is required for first 5% penetration of the intermittent capacity. However, for higher levels of penetration, the effective capacity (degree to which operators can rely on plants producing at a specific time) of intermittent resources is assumed to decrease. This is referred to as the capacity factor. This decrease leads to the need for backup power by low-cost options, such as gas turbines, the cost of which is allocated to the intermittent source.<br /> <br /> The required spinning reserve of the power system is the capacity that can be used to respond to a rapid increase in demand. This is assumed to be 3.5% of the installed capacity of a conventional power plant. If wind and solar power further penetrate the market, the model assumes an additional, required spinning reserve of 15% of the intermittent capacity (after subtraction of the 3.5% existing capacity). The related costs are allocated to the intermittent source.<br /> <br /> {{FormulaAndTableTemplate|Formula1_ED}}<br /> <br /> The costs of solar and wind power are the model determined by learning and depletion dynamics. For renewable energy, costs relate to capital, O&amp;M and system integration. The capital costs mostly relate to [[Energy conversion/Description/Technical learning|learning]] and depletion processes (learning is represented by so-called learning curves; depletion is represented by long-term cost–supply curves). <br /> <br /> The additional system integration costs relate to <br /> # Discarded electricity in cases where production exceeds demand and the overcapacity cannot be used within the system;<br /> # Back-up capacity;<br /> # Additional required spinning reserve;<br /> The two last items are needed to avoid loss of power if the supply of wind or solar power suddenly drops, enabling a power scale up in a relatively short time, in power stations operating below maximum capacity ([[Hoogwijk, 2004]]).<br /> *To determine discarded electricity, the model makes a comparison between 10 different points on the load-demand curve, at the overlap between demand and supply. For both wind and solar power, a typical load–supply curve is assumed (see [[Hoogwijk, 2004]]). If supply exceeds demand, the overcapacity in electricity is assumed to be discarded, resulting in higher production costs. <br /> *Because wind and solar power supply is intermittent (i.e. it varies and therefore is not reliable), the model assumes that so-called back-up capacity needs to be installed. For the first 5% penetration of the intermittent capacity, it is assumed that no-back is required. However, for higher levels of penetration, the effective capacity (i.e. degree to which operators can rely on plants producing at a particular moment in time) of intermittent resources is assumed to decrease (referred to as the capacity factor). This decrease leads to the need of back-up power(by low-cost options, such as gas turbines), the costs of which are allocated to the intermittent source.<br /> *The required spinning reserve of the power system (capacity that can be used to respond to a rapid increase in demand) is assumed to be 3.5% of the installed capacity of a conventional power plant. If wind and solar power further penetrate the market, the model assumes an additional, required spinning reserve of 15% of the intermittent capacity (but after first subtracting the 3.5% existing capacity). The related costs are allocated to the intermittent source.<br /> <br /> ==Nuclear power==<br /> For nuclear power, the costs also consists of capital, O&amp;M and nuclear fuel costs. Similar to the renewable energy options, technology improvement nuclear power is described via a learning curve (so costs decrease with cumulative installed capacity). At the same time, fuel costs increase as a function of depletion. Fuel costs are determined on the basis of the estimated extraction costs of uranium and thorium resources, as is described in the component [[Energy supply]]. A small trade model for these fission fuels is included.<br /> <br /> ==Hydrogen generation model==<br /> The structure of the hydrogen model is similar to that of the electric power model ([[Van Ruijven et al., 2007]]). There are, however, some important differences:<br /> *The hydrogen model distinguishes the following 11 supply options: hydrogen production plants on the basis of coal, oil, natural gas and bio-energy, with and <br /> without carbon capture and storage (8 plants), hydrogen production from electrolysis, direct hydrogen production from solar thermal processes, and, finally, small methane reform plants. <br /> *For simplification, no description of preferences for different power plants is accounted for in the operational strategy. In other words, the load factor for each option equals the total production divided by the capacity for each region.<br /> *Intermittence does not play an important role, as hydrogen can be stored to some degree. Therefore, there are no equations simulating system integration.<br /> *Hydrogen can be traded. Therefore, a trade model is added, similar to the trade models for fossil fuels, as is described in the [[Energy supply]] section.<br /> <br /> &lt;references/&gt;<br /> }}</div>

JoeriOostenrijk https://models.pbl.nl/index.php?title=Energy_conversion/Description&diff=21522 2014-05-08T16:31:42Z

<p>JoeriOostenrijk: </p> <hr /> <div>{{ComponentDescriptionTemplate<br /> |Reference=Hoogwijk, 2004; Van Vuuren, 2007; Hendriks et al., 2004b; Van Ruijven et al., 2007;<br /> |Description=[[TIMER model|TIMER]] includes two main energy conversion modules: Electric power generation and hydrogen generation. Below, electric power generation is described in detail. In addition, the key characteristics of the hydrogen generation model, which follows a similar structure, are presented.<br /> <br /> ==Electric power generation==<br /> As shown in the flowchart, two key elements of the electric power generation are the investment strategy and the operational strategy in the sector. A challenge in simulating electricity production in an aggregated model is that in reality electricity production depends on a range of complex factors, related to costs, reliance, and the time required to switch on technologies. Modelling these factors requires a high level of detail and thus {{AbbrTemplate|IAM}}s) such as [[TIMER model|TIMER]] concentrate on introducing a set of simplified, meta relationships ([[Hoogwijk, 2004]]; [[Van Vuuren, 2007]]).<br /> <br /> ===Total demand for new capacity===<br /> The electricity capacity required to meet the demand per region is based on a forecast of the maximum electricity demand plus a reserve margin of about 10% (including the capacity credit assigned to different forms of electricity generation). Maximum demand is calculated on the basis of an assumed monthly shape of the load duration curve (LDC) and the gross electricity demand. The latter comprises the net electricity demand from the end-use sectors plus electricity trade and transmission losses ({{AbbrTemplate|LDC}}) accounts for characteristics such as cooling and lighting demand). The demand for new generation capacity is the difference between the required and existing capacity. Power plants are assumed to be replaced at the end of their lifetime, which varies from 30 to 50 years, depending on the technology and is currently fixed in the model.<br /> <br /> ===Decisions to invest in specific options ===<br /> In the following step, a decision is made to invest in different generation technologies. In the model, this is done on the basis of the price of electricity (in USD/kWhe) produced per technology, using a multinomial logit equation that assigns larger market shares to the lower cost options. The specific costs of each option is broken down into a number of categories: investment or capital costs (USD/kWe), fuel costs (USD/GJ), operational and maintenance costs (OM) and other costs (see further). An exception is hydropower capacity, which is exogenously prescribed, because large hydropower plants often have functions other than only electricity production (e.g. water supply and flood control). In the equations, some constraints are added to account for limitations in supply (e.g. restrictions on biomass availability). The investments needed for each option are given in the form of total investment in new generation capacity and the share of each individual technology (determined on the basis of price and preference).<br /> <br /> ===Operational strategy===<br /> Use of power plants is based on operational costs, with low-cost technologies assumed to be used most often. This implies that capital-intensive plants with low operational costs, such as renewable and nuclear energy, operate as many hours as possible. To some degree, this is also true for other plants with low operational costs, such as coal. <br /> The operational decision is presented in the following three steps:<br /> #Renewable sources PV and wind are assigned, followed by hydropower, because these options have the lowest operational costs;<br /> #The peak load capacity (period of high electricity demand) is assigned on the basis of the operational costs of each available plant and the ability of these plants to provide peak load capacity; <br /> #Base load (period of medium to low energy demand) is assigned on the basis of the remaining capacity (after steps 1 and 2), operational costs and the ability of options to provide the base load capacity.<br /> <br /> <br /> ===Fossil-fuel and bio-energy power plants===<br /> A total of 20 types of power plants generating electricity using fossil fuels and bioenergy are included. These power plants represent different combinations of conventional technology, such as gasification and combined cycle (CC) technology; combined heat and power (CHP); and carbon capture and storage ([[CCS]];([[Hendriks et al., 2004b]]). The specific capital costs and thermal efficiencies of these types of plants are determined by exogenous assumptions that describe the technological progress of typical components of these plants:<br /> *For conventional power plants, the coal-fired plant is defined in terms of overall efficiency and investment cost. The characteristics of all other conventional plants (using oil, natural gas or bioenergy) are described in the investment differences for desulphurisation, fuel handling and efficiency.<br /> *For Combined Cycle (CC) power plants, the characteristics of a natural gas fired plant are set as the standard. Other CC plants (fuelled by oil, bioenergy and coal after gasification) are defined by indicating additional capital costs for gasification, efficiency losses due to gasification, and operation and maintenance (O&amp;M) costs for fuel handling. <br /> *Power plants with carbon-capture-and-storage systems (CCS) are assumed to be CC plants, but with fuel-specific lower efficiency and higher investment and O&amp;M costs (related to capture and storage). <br /> *The characteristics of combined-heat-and-power plants (CHP) are similar to those of other plants, but with an assumed small increase in capital costs, in combination with a lower efficiency for electric conversion and an added factor for heat efficiency. <br /> <br /> The cost of one unit electricity generated is equal to the sum of the capital cost, operational and maintenance costs (O&amp;M), fuel cost, and CO2 storage cost.<br /> <br /> ===Solar and wind power===<br /> <br /> The costs of solar and wind power in the model are determined by learning and depletion dynamics. For renewable energy, costs relate to capital, O&amp;M and system integration. The capital costs mostly relate to learning and depletion processes. Learning is represented by in learning curves (Box 4.1.3.1); depletion is by long-term in cost–supply curves. <br /> <br /> The additional system integration costs relate to curtailed electricity (if production exceeds demand and the overcapacity cannot be used within the system), backup capacity; and additional required spinning reserve. The last items are needed to avoid loss of power if the supply of wind or solar power drops suddenly, enabling a power scale up in a relatively short time, in power stations operating below maximum capacity ([[Hoogwijk, 2004]]).<br /> <br /> To determine curtailed electricity, the model compares 10 points on the load-demand curve at the overlap between demand and supply. For both wind and solar power, a typical load supply curve is assumed (see [[Hoogwijk, 2004]]). If supply exceeds demand, the overcapacity in electricity is assumed to be discarded, resulting in higher production costs.<br /> <br /> Because wind and solar power supply is intermittent (variable and thus not reliable), the model assumes that backup capacity needs to be installed. It is assumed that no backup is required for first 5% penetration of the intermittent capacity. However, for higher levels of penetration, the effective capacity (degree to which operators can rely on plants producing at a specific time) of intermittent resources is assumed to decrease. This is referred to as the capacity factor. This decrease leads to the need for backup power by low-cost options, such as gas turbines, the cost of which is allocated to the intermittent source.<br /> <br /> The required spinning reserve of the power system is the capacity that can be used to respond to a rapid increase in demand. This is assumed to be 3.5% of the installed capacity of a conventional power plant. If wind and solar power further penetrate the market, the model assumes an additional, required spinning reserve of 15% of the intermittent capacity (after subtraction of the 3.5% existing capacity). The related costs are allocated to the intermittent source.<br /> <br /> {{FormulaAndTableTemplate|Formula1_ED}}<br /> <br /> ==Nuclear power==<br /> The costs of nuclear power also include capital, O&amp;M and nuclear fuel costs. Similar to the renewable energy options, technology improvement in nuclear power is described via a learning curve (costs decrease with cumulative installed capacity). Fuel costs increase as a function of depletion. Fuel costs are determined on the basis of the estimated extraction costs for uranium and thorium resources, see [[Energy Supply]]. A small trade model for these fission fuels is included..<br /> <br /> ==Hydrogen generation model==<br /> The structure of the hydrogen generation submodule is similar to that for electric power generation ([[Van Ruijven et al., 2007]]) but with following differences:<br /> *There are only eleven supply options for hydrogen production coal, oil, natural gas and bioenergy, with and without carbon capture and storage (8 plants); hydrogen production from electrolysis, direct hydrogen production from solar thermal processes; and small methane reform plants. <br /> *No description of preferences for different power plants is taken into account in the operational strategy. The load factor for each option equals the total production divided by the capacity for each region.<br /> *Intermittence does not play an important role because hydrogen can be stored to some degree. Thus, there are no equations simulating system integration.<br /> *Hydrogen can be traded. A trade model is added, similar to those for fossil fuels described in [[Energy Supply]].<br /> <br /> ===Total demand for new capacity===<br /> The electricity capacity required to meet the demand per region is based on a forecast of the maximum electricity demand plus a reserve margin of about 10% (including the capacity credit assigned to different forms of electricity generation). Maximum demand is calculated on the basis of an assumed monthly shape of the load duration curve (LDC) and the gross electricity demand. The latter comprises the net electricity demand from the end-use sectors plus electricity trade and transmission losses ({{AbbrTemplate|LDC}}) accounts for characteristics such as cooling and lighting demand). The demand for new generation capacity is the difference between the required and existing capacity. Power plants are assumed to be replaced at the end of their lifetime, which varies from 30 to 50 years, depending on the technology and is currently fixed in the model.<br /> <br /> ===Decisions to invest in specific options ===<br /> In the following step, a decision is made to invest in different generation technologies. In the model, this is done on the basis of the price of electricity (in {{AbbrTemplate|USD/kWhe}} produced per technology, using a multinomial logit equation that assigns larger market shares to the lower cost options. The specific costs of each option is broken down into a number of categories: investment or capital costs (USD/kWe), fuel costs ([[HasAcronym::USD/GJ]]), operational and maintenance costs (OM) and other costs (see further). An exception is hydropower capacity, which is exogenously prescribed, because large hydropower plants often have functions other than only electricity production (e.g. water supply and flood control). In the equations, some constraints are added to account for limitations in supply (e.g. restrictions on biomass availability). The investments needed for each option are given in the form of total investment in new generation capacity and the share of each individual technology (determined on the basis of price and preference).<br /> <br /> ===Operational strategy===<br /> Use of power plants is based on operational costs, with low-cost technologies assumed to be used most often. This implies that capital-intensive plants with low operational costs, such as renewable and nuclear energy, operate as many hours as possible. To some degree, this is also true for other plants with low operational costs, such as coal. <br /> The operational decision is presented in the following three steps:<br /> #Renewable sources PV and wind are assigned, followed by hydropower, because these options have the lowest operational costs;<br /> #The peak load capacity (period of high electricity demand) is assigned on the basis of the operational costs of each available plant and the ability of these plants to provide peak load capacity; <br /> #Base load (period of medium to low energy demand) is assigned on the basis of the remaining capacity (after steps 1 and 2), operational costs and the ability of options to provide the base load capacity.<br /> <br /> <br /> ===Fossil-fuel and bio-energy power plants===<br /> A total of 20 types of power plants generating electricity using fossil fuels and bioenergy are included. These power plants represent different combinations of conventional technology, such as gasification and combined cycle (CC) technology; combined heat and power (CHP); and carbon capture and storage (CCS;(Hendriks et al., 2004b). The specific capital costs and thermal efficiencies of these types of plants are determined by exogenous assumptions that describe the technological progress of typical components of these plants:<br /> *For conventional power plants, the coal-fired plant is defined in terms of overall efficiency and investment cost. The characteristics of all other conventional plants (using oil, natural gas or bioenergy) are described in the investment differences for desulphurisation, fuel handling and efficiency.<br /> *For Combined Cycle (CC) power plants, the characteristics of a natural gas fired plant are set as the standard. Other CC plants (fuelled by oil, bioenergy and coal after gasification) are defined by indicating additional capital costs for gasification, efficiency losses due to gasification, and operation and maintenance (O&amp;M) costs for fuel handling. <br /> *Power plants with carbon-capture-and-storage systems (CCS) are assumed to be CC plants, but with fuel-specific lower efficiency and higher investment and O&amp;M costs (related to capture and storage). <br /> *The characteristics of combined-heat-and-power plants (CHP) are similar to those of other plants, but with an assumed small increase in capital costs, in combination with a lower efficiency for electric conversion and an added factor for heat efficiency. <br /> <br /> The cost of one unit electricity generated is equal to the sum of the capital cost, operational and maintenance costs (O&amp;M), fuel cost, and CO2 storage cost.<br /> <br /> ===Solar and wind power===<br /> <br /> The costs of solar and wind power in the model are determined by learning and depletion dynamics. For renewable energy, costs relate to capital, O&amp;M and system integration. The capital costs mostly relate to learning and depletion processes. Learning is represented by in learning curves (Box 4.1.3.1); depletion is by long-term in cost–supply curves. <br /> <br /> The additional system integration costs relate to curtailed electricity (if production exceeds demand and the overcapacity cannot be used within the system), backup capacity; and additional required spinning reserve. The last items are needed to avoid loss of power if the supply of wind or solar power drops suddenly, enabling a power scale up in a relatively short time, in power stations operating below maximum capacity ([[Hoogwijk, 2004]]).<br /> <br /> To determine curtailed electricity, the model compares 10 points on the load-demand curve at the overlap between demand and supply. For both wind and solar power, a typical load supply curve is assumed (see [[Hoogwijk, 2004]]). If supply exceeds demand, the overcapacity in electricity is assumed to be discarded, resulting in higher production costs.<br /> <br /> Because wind and solar power supply is intermittent (variable and thus not reliable), the model assumes that backup capacity needs to be installed. It is assumed that no backup is required for first 5% penetration of the intermittent capacity. However, for higher levels of penetration, the effective capacity (degree to which operators can rely on plants producing at a specific time) of intermittent resources is assumed to decrease. This is referred to as the capacity factor. This decrease leads to the need for backup power by low-cost options, such as gas turbines, the cost of which is allocated to the intermittent source.<br /> <br /> The required spinning reserve of the power system is the capacity that can be used to respond to a rapid increase in demand. This is assumed to be 3.5% of the installed capacity of a conventional power plant. If wind and solar power further penetrate the market, the model assumes an additional, required spinning reserve of 15% of the intermittent capacity (after subtraction of the 3.5% existing capacity). The related costs are allocated to the intermittent source.<br /> <br /> <br /> {{FormulaAndTableTemplate|Formula1_ED}}<br /> <br /> The costs of solar and wind power are the model determined by learning and depletion dynamics. For renewable energy, costs relate to capital, O&amp;M and system integration. The capital costs mostly relate to [[Energy conversion/Description/Technical learning|learning]] and depletion processes (learning is represented by so-called learning curves; depletion is represented by long-term cost–supply curves). <br /> <br /> The additional system integration costs relate to <br /> # Discarded electricity in cases where production exceeds demand and the overcapacity cannot be used within the system;<br /> # Back-up capacity;<br /> # Additional required spinning reserve;<br /> The two last items are needed to avoid loss of power if the supply of wind or solar power suddenly drops, enabling a power scale up in a relatively short time, in power stations operating below maximum capacity ([[Hoogwijk, 2004]]).<br /> *To determine discarded electricity, the model makes a comparison between 10 different points on the load-demand curve, at the overlap between demand and supply. For both wind and solar power, a typical load–supply curve is assumed (see [[Hoogwijk, 2004]]). If supply exceeds demand, the overcapacity in electricity is assumed to be discarded, resulting in higher production costs. <br /> *Because wind and solar power supply is intermittent (i.e. it varies and therefore is not reliable), the model assumes that so-called back-up capacity needs to be installed. For the first 5% penetration of the intermittent capacity, it is assumed that no-back is required. However, for higher levels of penetration, the effective capacity (i.e. degree to which operators can rely on plants producing at a particular moment in time) of intermittent resources is assumed to decrease (referred to as the capacity factor). This decrease leads to the need of back-up power(by low-cost options, such as gas turbines), the costs of which are allocated to the intermittent source.<br /> *The required spinning reserve of the power system (capacity that can be used to respond to a rapid increase in demand) is assumed to be 3.5% of the installed capacity of a conventional power plant. If wind and solar power further penetrate the market, the model assumes an additional, required spinning reserve of 15% of the intermittent capacity (but after first subtracting the 3.5% existing capacity). The related costs are allocated to the intermittent source.<br /> <br /> ==Nuclear power==<br /> For nuclear power, the costs also consists of capital, O&amp;M and nuclear fuel costs. Similar to the renewable energy options, technology improvement nuclear power is described via a learning curve (so costs decrease with cumulative installed capacity). At the same time, fuel costs increase as a function of depletion. Fuel costs are determined on the basis of the estimated extraction costs of uranium and thorium resources, as is described in the component [[Energy supply]]. A small trade model for these fission fuels is included.<br /> <br /> ==Hydrogen generation model==<br /> The structure of the hydrogen model is similar to that of the electric power model ([[Van Ruijven et al., 2007]]). There are, however, some important differences:<br /> *The hydrogen model distinguishes the following 11 supply options: hydrogen production plants on the basis of coal, oil, natural gas and bio-energy, with and <br /> without carbon capture and storage (8 plants), hydrogen production from electrolysis, direct hydrogen production from solar thermal processes, and, finally, small methane reform plants. <br /> *For simplification, no description of preferences for different power plants is accounted for in the operational strategy. In other words, the load factor for each option equals the total production divided by the capacity for each region.<br /> *Intermittence does not play an important role, as hydrogen can be stored to some degree. Therefore, there are no equations simulating system integration.<br /> *Hydrogen can be traded. Therefore, a trade model is added, similar to the trade models for fossil fuels, as is described in the [[Energy supply]] section.<br /> <br /> &lt;references/&gt;<br /> }}</div>

JoeriOostenrijk https://models.pbl.nl/index.php?title=Energy_conversion/Description&diff=21521 2014-05-08T16:30:39Z

<p>JoeriOostenrijk: </p> <hr /> <div>{{ComponentDescriptionTemplate<br /> |Reference=Hoogwijk, 2004; Van Vuuren, 2007; Hendriks et al., 2004b; Van Ruijven et al., 2007;<br /> |Description=[[TIMER model|TIMER]] includes two main energy conversion modules: Electric power generation and hydrogen generation. Below, electric power generation is described in detail. In addition, the key characteristics of the hydrogen generation model, which follows a similar structure, are presented.<br /> <br /> ==Electric power generation==<br /> As shown in the flowchart, two key elements of the electric power generation are the investment strategy and the operational strategy in the sector. A challenge in simulating electricity production in an aggregated model is that in reality electricity production depends on a range of complex factors, related to costs, reliance, and the time required to switch on technologies. Modelling these factors requires a high level of detail and thus {{AbbrTemplate|IAM}}s) such as [[TIMER model|TIMER]] concentrate on introducing a set of simplified, meta relationships ([[Hoogwijk, 2004]]; [[Van Vuuren, 2007]]).<br /> <br /> ===Total demand for new capacity===<br /> The electricity capacity required to meet the demand per region is based on a forecast of the maximum electricity demand plus a reserve margin of about 10% (including the capacity credit assigned to different forms of electricity generation). Maximum demand is calculated on the basis of an assumed monthly shape of the load duration curve (LDC) and the gross electricity demand. The latter comprises the net electricity demand from the end-use sectors plus electricity trade and transmission losses ({{AbbrTemplate|LDC}}) accounts for characteristics such as cooling and lighting demand). The demand for new generation capacity is the difference between the required and existing capacity. Power plants are assumed to be replaced at the end of their lifetime, which varies from 30 to 50 years, depending on the technology and is currently fixed in the model.<br /> <br /> ===Decisions to invest in specific options ===<br /> In the following step, a decision is made to invest in different generation technologies. In the model, this is done on the basis of the price of electricity (in USD/kWhe) produced per technology, using a multinomial logit equation that assigns larger market shares to the lower cost options. The specific costs of each option is broken down into a number of categories: investment or capital costs (USD/kWe), fuel costs (USD/GJ), operational and maintenance costs (OM) and other costs (see further). An exception is hydropower capacity, which is exogenously prescribed, because large hydropower plants often have functions other than only electricity production (e.g. water supply and flood control). In the equations, some constraints are added to account for limitations in supply (e.g. restrictions on biomass availability). The investments needed for each option are given in the form of total investment in new generation capacity and the share of each individual technology (determined on the basis of price and preference).<br /> <br /> ===Operational strategy===<br /> Use of power plants is based on operational costs, with low-cost technologies assumed to be used most often. This implies that capital-intensive plants with low operational costs, such as renewable and nuclear energy, operate as many hours as possible. To some degree, this is also true for other plants with low operational costs, such as coal. <br /> The operational decision is presented in the following three steps:<br /> #Renewable sources PV and wind are assigned, followed by hydropower, because these options have the lowest operational costs;<br /> #The peak load capacity (period of high electricity demand) is assigned on the basis of the operational costs of each available plant and the ability of these plants to provide peak load capacity; <br /> #Base load (period of medium to low energy demand) is assigned on the basis of the remaining capacity (after steps 1 and 2), operational costs and the ability of options to provide the base load capacity.<br /> <br /> <br /> ===Fossil-fuel and bio-energy power plants===<br /> A total of 20 types of power plants generating electricity using fossil fuels and bioenergy are included. These power plants represent different combinations of conventional technology, such as gasification and combined cycle (CC) technology; combined heat and power (CHP); and carbon capture and storage ([[CCS]];([[Hendriks et al., 2004b]]). The specific capital costs and thermal efficiencies of these types of plants are determined by exogenous assumptions that describe the technological progress of typical components of these plants:<br /> *For conventional power plants, the coal-fired plant is defined in terms of overall efficiency and investment cost. The characteristics of all other conventional plants (using oil, natural gas or bioenergy) are described in the investment differences for desulphurisation, fuel handling and efficiency.<br /> *For Combined Cycle (CC) power plants, the characteristics of a natural gas fired plant are set as the standard. Other CC plants (fuelled by oil, bioenergy and coal after gasification) are defined by indicating additional capital costs for gasification, efficiency losses due to gasification, and operation and maintenance (O&amp;M) costs for fuel handling. <br /> *Power plants with carbon-capture-and-storage systems (CCS) are assumed to be CC plants, but with fuel-specific lower efficiency and higher investment and O&amp;M costs (related to capture and storage). <br /> *The characteristics of combined-heat-and-power plants (CHP) are similar to those of other plants, but with an assumed small increase in capital costs, in combination with a lower efficiency for electric conversion and an added factor for heat efficiency. <br /> <br /> The cost of one unit electricity generated is equal to the sum of the capital cost, operational and maintenance costs (O&amp;M), fuel cost, and CO2 storage cost.<br /> <br /> ===Solar and wind power===<br /> <br /> The costs of solar and wind power in the model are determined by learning and depletion dynamics. For renewable energy, costs relate to capital, O&amp;M and system integration. The capital costs mostly relate to learning and depletion processes. Learning is represented by in learning curves (Box 4.1.3.1); depletion is by long-term in cost–supply curves. <br /> <br /> The additional system integration costs relate to curtailed electricity (if production exceeds demand and the overcapacity cannot be used within the system), backup capacity; and additional required spinning reserve. The last items are needed to avoid loss of power if the supply of wind or solar power drops suddenly, enabling a power scale up in a relatively short time, in power stations operating below maximum capacity ([[Hoogwijk, 2004]]).<br /> <br /> To determine curtailed electricity, the model compares 10 points on the load-demand curve at the overlap between demand and supply. For both wind and solar power, a typical load supply curve is assumed (see [[Hoogwijk, 2004]]). If supply exceeds demand, the overcapacity in electricity is assumed to be discarded, resulting in higher production costs.<br /> <br /> Because wind and solar power supply is intermittent (variable and thus not reliable), the model assumes that backup capacity needs to be installed. It is assumed that no backup is required for first 5% penetration of the intermittent capacity. However, for higher levels of penetration, the effective capacity (degree to which operators can rely on plants producing at a specific time) of intermittent resources is assumed to decrease. This is referred to as the capacity factor. This decrease leads to the need for backup power by low-cost options, such as gas turbines, the cost of which is allocated to the intermittent source.<br /> <br /> The required spinning reserve of the power system is the capacity that can be used to respond to a rapid increase in demand. This is assumed to be 3.5% of the installed capacity of a conventional power plant. If wind and solar power further penetrate the market, the model assumes an additional, required spinning reserve of 15% of the intermittent capacity (after subtraction of the 3.5% existing capacity). The related costs are allocated to the intermittent source.<br /> <br /> {{FormulaAndTableTemplate|Formula1_ED}}<br /> <br /> ==Nuclear power==<br /> The costs of nuclear power also include capital, O&amp;M and nuclear fuel costs. Similar to the renewable energy options, technology improvement in nuclear power is described via a learning curve (costs decrease with cumulative installed capacity). Fuel costs increase as a function of depletion. Fuel costs are determined on the basis of the estimated extraction costs for uranium and thorium resources, see [[Energy Supply]]. A small trade model for these fission fuels is included..<br /> <br /> ==Hydrogen generation model==<br /> The structure of the hydrogen generation submodule is similar to that for electric power generation ([[Van Ruijven et al., 2007]]) but with following differences:<br /> *There are only eleven supply options for hydrogen production coal, oil, natural gas and bioenergy, with and without carbon capture and storage (8 plants); hydrogen production from electrolysis, direct hydrogen production from solar thermal processes; and small methane reform plants. <br /> *No description of preferences for different power plants is taken into account in the operational strategy. The load factor for each option equals the total production divided by the capacity for each region.<br /> *Intermittence does not play an important role because hydrogen can be stored to some degree. Thus, there are no equations simulating system integration.<br /> *Hydrogen can be traded. A trade model is added, similar to those for fossil fuels described in [[Energy Supply]].<br /> <br /> <br /> }}<br /> }}<br /> }}<br /> s such as [[TIMER model|TIMER]] concentrate on introducing a set of simplified, meta relationships ([[Hoogwijk, 2004]]; [[Van Vuuren, 2007]]).<br /> <br /> ===Total demand for new capacity===<br /> The electricity capacity required to meet the demand per region is based on a forecast of the maximum electricity demand plus a reserve margin of about 10% (including the capacity credit assigned to different forms of electricity generation). Maximum demand is calculated on the basis of an assumed monthly shape of the load duration curve (LDC) and the gross electricity demand. The latter comprises the net electricity demand from the end-use sectors plus electricity trade and transmission losses ({{AbbrTemplate|LDC}}) accounts for characteristics such as cooling and lighting demand). The demand for new generation capacity is the difference between the required and existing capacity. Power plants are assumed to be replaced at the end of their lifetime, which varies from 30 to 50 years, depending on the technology and is currently fixed in the model.<br /> <br /> ===Decisions to invest in specific options ===<br /> In the following step, a decision is made to invest in different generation technologies. In the model, this is done on the basis of the price of electricity (in {{AbbrTemplate|USD/kWhe}} produced per technology, using a multinomial logit equation that assigns larger market shares to the lower cost options. The specific costs of each option is broken down into a number of categories: investment or capital costs (USD/kWe), fuel costs ([[HasAcronym::USD/GJ]]), operational and maintenance costs (OM) and other costs (see further). An exception is hydropower capacity, which is exogenously prescribed, because large hydropower plants often have functions other than only electricity production (e.g. water supply and flood control). In the equations, some constraints are added to account for limitations in supply (e.g. restrictions on biomass availability). The investments needed for each option are given in the form of total investment in new generation capacity and the share of each individual technology (determined on the basis of price and preference).<br /> <br /> ===Operational strategy===<br /> Use of power plants is based on operational costs, with low-cost technologies assumed to be used most often. This implies that capital-intensive plants with low operational costs, such as renewable and nuclear energy, operate as many hours as possible. To some degree, this is also true for other plants with low operational costs, such as coal. <br /> The operational decision is presented in the following three steps:<br /> #Renewable sources PV and wind are assigned, followed by hydropower, because these options have the lowest operational costs;<br /> #The peak load capacity (period of high electricity demand) is assigned on the basis of the operational costs of each available plant and the ability of these plants to provide peak load capacity; <br /> #Base load (period of medium to low energy demand) is assigned on the basis of the remaining capacity (after steps 1 and 2), operational costs and the ability of options to provide the base load capacity.<br /> <br /> <br /> ===Fossil-fuel and bio-energy power plants===<br /> A total of 20 types of power plants generating electricity using fossil fuels and bioenergy are included. These power plants represent different combinations of conventional technology, such as gasification and combined cycle (CC) technology; combined heat and power (CHP); and carbon capture and storage (CCS;(Hendriks et al., 2004b). The specific capital costs and thermal efficiencies of these types of plants are determined by exogenous assumptions that describe the technological progress of typical components of these plants:<br /> *For conventional power plants, the coal-fired plant is defined in terms of overall efficiency and investment cost. The characteristics of all other conventional plants (using oil, natural gas or bioenergy) are described in the investment differences for desulphurisation, fuel handling and efficiency.<br /> *For Combined Cycle (CC) power plants, the characteristics of a natural gas fired plant are set as the standard. Other CC plants (fuelled by oil, bioenergy and coal after gasification) are defined by indicating additional capital costs for gasification, efficiency losses due to gasification, and operation and maintenance (O&amp;M) costs for fuel handling. <br /> *Power plants with carbon-capture-and-storage systems (CCS) are assumed to be CC plants, but with fuel-specific lower efficiency and higher investment and O&amp;M costs (related to capture and storage). <br /> *The characteristics of combined-heat-and-power plants (CHP) are similar to those of other plants, but with an assumed small increase in capital costs, in combination with a lower efficiency for electric conversion and an added factor for heat efficiency. <br /> <br /> The cost of one unit electricity generated is equal to the sum of the capital cost, operational and maintenance costs (O&amp;M), fuel cost, and CO2 storage cost.<br /> <br /> ===Solar and wind power===<br /> <br /> The costs of solar and wind power in the model are determined by learning and depletion dynamics. For renewable energy, costs relate to capital, O&amp;M and system integration. The capital costs mostly relate to learning and depletion processes. Learning is represented by in learning curves (Box 4.1.3.1); depletion is by long-term in cost–supply curves. <br /> <br /> The additional system integration costs relate to curtailed electricity (if production exceeds demand and the overcapacity cannot be used within the system), backup capacity; and additional required spinning reserve. The last items are needed to avoid loss of power if the supply of wind or solar power drops suddenly, enabling a power scale up in a relatively short time, in power stations operating below maximum capacity ([[Hoogwijk, 2004]]).<br /> <br /> To determine curtailed electricity, the model compares 10 points on the load-demand curve at the overlap between demand and supply. For both wind and solar power, a typical load supply curve is assumed (see [[Hoogwijk, 2004]]). If supply exceeds demand, the overcapacity in electricity is assumed to be discarded, resulting in higher production costs.<br /> <br /> Because wind and solar power supply is intermittent (variable and thus not reliable), the model assumes that backup capacity needs to be installed. It is assumed that no backup is required for first 5% penetration of the intermittent capacity. However, for higher levels of penetration, the effective capacity (degree to which operators can rely on plants producing at a specific time) of intermittent resources is assumed to decrease. This is referred to as the capacity factor. This decrease leads to the need for backup power by low-cost options, such as gas turbines, the cost of which is allocated to the intermittent source.<br /> <br /> The required spinning reserve of the power system is the capacity that can be used to respond to a rapid increase in demand. This is assumed to be 3.5% of the installed capacity of a conventional power plant. If wind and solar power further penetrate the market, the model assumes an additional, required spinning reserve of 15% of the intermittent capacity (after subtraction of the 3.5% existing capacity). The related costs are allocated to the intermittent source.<br /> <br /> <br /> {{FormulaAndTableTemplate|Formula1_ED}}<br /> <br /> The costs of solar and wind power are the model determined by learning and depletion dynamics. For renewable energy, costs relate to capital, O&amp;M and system integration. The capital costs mostly relate to [[Energy conversion/Description/Technical learning|learning]] and depletion processes (learning is represented by so-called learning curves; depletion is represented by long-term cost–supply curves). <br /> <br /> The additional system integration costs relate to <br /> # Discarded electricity in cases where production exceeds demand and the overcapacity cannot be used within the system;<br /> # Back-up capacity;<br /> # Additional required spinning reserve;<br /> The two last items are needed to avoid loss of power if the supply of wind or solar power suddenly drops, enabling a power scale up in a relatively short time, in power stations operating below maximum capacity ([[Hoogwijk, 2004]]).<br /> *To determine discarded electricity, the model makes a comparison between 10 different points on the load-demand curve, at the overlap between demand and supply. For both wind and solar power, a typical load–supply curve is assumed (see [[Hoogwijk, 2004]]). If supply exceeds demand, the overcapacity in electricity is assumed to be discarded, resulting in higher production costs. <br /> *Because wind and solar power supply is intermittent (i.e. it varies and therefore is not reliable), the model assumes that so-called back-up capacity needs to be installed. For the first 5% penetration of the intermittent capacity, it is assumed that no-back is required. However, for higher levels of penetration, the effective capacity (i.e. degree to which operators can rely on plants producing at a particular moment in time) of intermittent resources is assumed to decrease (referred to as the capacity factor). This decrease leads to the need of back-up power(by low-cost options, such as gas turbines), the costs of which are allocated to the intermittent source.<br /> *The required spinning reserve of the power system (capacity that can be used to respond to a rapid increase in demand) is assumed to be 3.5% of the installed capacity of a conventional power plant. If wind and solar power further penetrate the market, the model assumes an additional, required spinning reserve of 15% of the intermittent capacity (but after first subtracting the 3.5% existing capacity). The related costs are allocated to the intermittent source.<br /> <br /> ==Nuclear power==<br /> For nuclear power, the costs also consists of capital, O&amp;M and nuclear fuel costs. Similar to the renewable energy options, technology improvement nuclear power is described via a learning curve (so costs decrease with cumulative installed capacity). At the same time, fuel costs increase as a function of depletion. Fuel costs are determined on the basis of the estimated extraction costs of uranium and thorium resources, as is described in the component [[Energy supply]]. A small trade model for these fission fuels is included.<br /> <br /> ==Hydrogen generation model==<br /> The structure of the hydrogen model is similar to that of the electric power model ([[Van Ruijven et al., 2007]]). There are, however, some important differences:<br /> *The hydrogen model distinguishes the following 11 supply options: hydrogen production plants on the basis of coal, oil, natural gas and bio-energy, with and <br /> without carbon capture and storage (8 plants), hydrogen production from electrolysis, direct hydrogen production from solar thermal processes, and, finally, small methane reform plants. <br /> *For simplification, no description of preferences for different power plants is accounted for in the operational strategy. In other words, the load factor for each option equals the total production divided by the capacity for each region.<br /> *Intermittence does not play an important role, as hydrogen can be stored to some degree. Therefore, there are no equations simulating system integration.<br /> *Hydrogen can be traded. Therefore, a trade model is added, similar to the trade models for fossil fuels, as is described in the [[Energy supply]] section.<br /> <br /> &lt;references/&gt;</div>

JoeriOostenrijk https://models.pbl.nl/index.php?title=Energy_conversion/Description&diff=21520 2014-05-08T16:30:11Z

<p>JoeriOostenrijk: </p> <hr /> <div>{{ComponentDescriptionTemplate<br /> |Reference=Hoogwijk, 2004; Van Vuuren, 2007; Hendriks et al., 2004b; Van Ruijven et al., 2007;<br /> |Description=[[TIMER model|TIMER]] includes two main energy conversion modules: Electric power generation and hydrogen generation. Below, electric power generation is described in detail. In addition, the key characteristics of the hydrogen generation model, which follows a similar structure, are presented.<br /> <br /> ==Electric power generation==<br /> As shown in the flowchart, two key elements of the electric power generation are the investment strategy and the operational strategy in the sector. A challenge in simulating electricity production in an aggregated model is that in reality electricity production depends on a range of complex factors, related to costs, reliance, and the time required to switch on technologies. Modelling these factors requires a high level of detail and thus {{AbbrTemplate|IAM}}s) such as [[TIMER model|TIMER]] concentrate on introducing a set of simplified, meta relationships ([[Hoogwijk, 2004]]; [[Van Vuuren, 2007]]).<br /> <br /> ===Total demand for new capacity===<br /> The electricity capacity required to meet the demand per region is based on a forecast of the maximum electricity demand plus a reserve margin of about 10% (including the capacity credit assigned to different forms of electricity generation). Maximum demand is calculated on the basis of an assumed monthly shape of the load duration curve (LDC) and the gross electricity demand. The latter comprises the net electricity demand from the end-use sectors plus electricity trade and transmission losses ({{AbbrTemplate|LDC}}) accounts for characteristics such as cooling and lighting demand). The demand for new generation capacity is the difference between the required and existing capacity. Power plants are assumed to be replaced at the end of their lifetime, which varies from 30 to 50 years, depending on the technology and is currently fixed in the model.<br /> <br /> ===Decisions to invest in specific options ===<br /> In the following step, a decision is made to invest in different generation technologies. In the model, this is done on the basis of the price of electricity (in USD/kWhe) produced per technology, using a multinomial logit equation that assigns larger market shares to the lower cost options. The specific costs of each option is broken down into a number of categories: investment or capital costs (USD/kWe), fuel costs (USD/GJ), operational and maintenance costs (OM) and other costs (see further). An exception is hydropower capacity, which is exogenously prescribed, because large hydropower plants often have functions other than only electricity production (e.g. water supply and flood control). In the equations, some constraints are added to account for limitations in supply (e.g. restrictions on biomass availability). The investments needed for each option are given in the form of total investment in new generation capacity and the share of each individual technology (determined on the basis of price and preference).<br /> <br /> ===Operational strategy===<br /> Use of power plants is based on operational costs, with low-cost technologies assumed to be used most often. This implies that capital-intensive plants with low operational costs, such as renewable and nuclear energy, operate as many hours as possible. To some degree, this is also true for other plants with low operational costs, such as coal. <br /> The operational decision is presented in the following three steps:<br /> #Renewable sources PV and wind are assigned, followed by hydropower, because these options have the lowest operational costs;<br /> #The peak load capacity (period of high electricity demand) is assigned on the basis of the operational costs of each available plant and the ability of these plants to provide peak load capacity; <br /> #Base load (period of medium to low energy demand) is assigned on the basis of the remaining capacity (after steps 1 and 2), operational costs and the ability of options to provide the base load capacity.<br /> <br /> <br /> ===Fossil-fuel and bio-energy power plants===<br /> A total of 20 types of power plants generating electricity using fossil fuels and bioenergy are included. These power plants represent different combinations of conventional technology, such as gasification and combined cycle (CC) technology; combined heat and power (CHP); and carbon capture and storage ([[CCS]];([[Hendriks et al., 2004b]]). The specific capital costs and thermal efficiencies of these types of plants are determined by exogenous assumptions that describe the technological progress of typical components of these plants:<br /> *For conventional power plants, the coal-fired plant is defined in terms of overall efficiency and investment cost. The characteristics of all other conventional plants (using oil, natural gas or bioenergy) are described in the investment differences for desulphurisation, fuel handling and efficiency.<br /> *For Combined Cycle (CC) power plants, the characteristics of a natural gas fired plant are set as the standard. Other CC plants (fuelled by oil, bioenergy and coal after gasification) are defined by indicating additional capital costs for gasification, efficiency losses due to gasification, and operation and maintenance (O&amp;M) costs for fuel handling. <br /> *Power plants with carbon-capture-and-storage systems (CCS) are assumed to be CC plants, but with fuel-specific lower efficiency and higher investment and O&amp;M costs (related to capture and storage). <br /> *The characteristics of combined-heat-and-power plants (CHP) are similar to those of other plants, but with an assumed small increase in capital costs, in combination with a lower efficiency for electric conversion and an added factor for heat efficiency. <br /> <br /> The cost of one unit electricity generated is equal to the sum of the capital cost, operational and maintenance costs (O&amp;M), fuel cost, and CO2 storage cost.<br /> <br /> ===Solar and wind power===<br /> <br /> The costs of solar and wind power in the model are determined by learning and depletion dynamics. For renewable energy, costs relate to capital, O&amp;M and system integration. The capital costs mostly relate to learning and depletion processes. Learning is represented by in learning curves (Box 4.1.3.1); depletion is by long-term in cost–supply curves. <br /> <br /> The additional system integration costs relate to curtailed electricity (if production exceeds demand and the overcapacity cannot be used within the system), backup capacity; and additional required spinning reserve. The last items are needed to avoid loss of power if the supply of wind or solar power drops suddenly, enabling a power scale up in a relatively short time, in power stations operating below maximum capacity ([[Hoogwijk, 2004]]).<br /> <br /> To determine curtailed electricity, the model compares 10 points on the load-demand curve at the overlap between demand and supply. For both wind and solar power, a typical load supply curve is assumed (see [[Hoogwijk, 2004]]). If supply exceeds demand, the overcapacity in electricity is assumed to be discarded, resulting in higher production costs.<br /> <br /> Because wind and solar power supply is intermittent (variable and thus not reliable), the model assumes that backup capacity needs to be installed. It is assumed that no backup is required for first 5% penetration of the intermittent capacity. However, for higher levels of penetration, the effective capacity (degree to which operators can rely on plants producing at a specific time) of intermittent resources is assumed to decrease. This is referred to as the capacity factor. This decrease leads to the need for backup power by low-cost options, such as gas turbines, the cost of which is allocated to the intermittent source.<br /> <br /> The required spinning reserve of the power system is the capacity that can be used to respond to a rapid increase in demand. This is assumed to be 3.5% of the installed capacity of a conventional power plant. If wind and solar power further penetrate the market, the model assumes an additional, required spinning reserve of 15% of the intermittent capacity (after subtraction of the 3.5% existing capacity). The related costs are allocated to the intermittent source.<br /> <br /> {{FormulaAndTableTemplate|Formula1_ED}}<br /> <br /> ==Nuclear power==<br /> The costs of nuclear power also include capital, O&amp;M and nuclear fuel costs. Similar to the renewable energy options, technology improvement in nuclear power is described via a learning curve (costs decrease with cumulative installed capacity). Fuel costs increase as a function of depletion. Fuel costs are determined on the basis of the estimated extraction costs for uranium and thorium resources, see [[Energy Supply]]. A small trade model for these fission fuels is included..<br /> <br /> ==Hydrogen generation model==<br /> The structure of the hydrogen generation submodule is similar to that for electric power generation ([[Van Ruijven et al., 2007]]) but with following differences:<br /> *There are only eleven supply options for hydrogen production coal, oil, natural gas and bioenergy, with and without carbon capture and storage (8 plants); hydrogen production from electrolysis, direct hydrogen production from solar thermal processes; and small methane reform plants. <br /> *No description of preferences for different power plants is taken into account in the operational strategy. The load factor for each option equals the total production divided by the capacity for each region.<br /> *Intermittence does not play an important role because hydrogen can be stored to some degree. Thus, there are no equations simulating system integration.<br /> *Hydrogen can be traded. A trade model is added, similar to those for fossil fuels described in [[Energy Supply]].<br /> <br /> &lt;references/&gt;<br /> }}<br /> <br /> }}<br /> }}<br /> s such as [[TIMER model|TIMER]] concentrate on introducing a set of simplified, meta relationships ([[Hoogwijk, 2004]]; [[Van Vuuren, 2007]]).<br /> <br /> ===Total demand for new capacity===<br /> The electricity capacity required to meet the demand per region is based on a forecast of the maximum electricity demand plus a reserve margin of about 10% (including the capacity credit assigned to different forms of electricity generation). Maximum demand is calculated on the basis of an assumed monthly shape of the load duration curve (LDC) and the gross electricity demand. The latter comprises the net electricity demand from the end-use sectors plus electricity trade and transmission losses ({{AbbrTemplate|LDC}}) accounts for characteristics such as cooling and lighting demand). The demand for new generation capacity is the difference between the required and existing capacity. Power plants are assumed to be replaced at the end of their lifetime, which varies from 30 to 50 years, depending on the technology and is currently fixed in the model.<br /> <br /> ===Decisions to invest in specific options ===<br /> In the following step, a decision is made to invest in different generation technologies. In the model, this is done on the basis of the price of electricity (in {{AbbrTemplate|USD/kWhe}} produced per technology, using a multinomial logit equation that assigns larger market shares to the lower cost options. The specific costs of each option is broken down into a number of categories: investment or capital costs (USD/kWe), fuel costs ([[HasAcronym::USD/GJ]]), operational and maintenance costs (OM) and other costs (see further). An exception is hydropower capacity, which is exogenously prescribed, because large hydropower plants often have functions other than only electricity production (e.g. water supply and flood control). In the equations, some constraints are added to account for limitations in supply (e.g. restrictions on biomass availability). The investments needed for each option are given in the form of total investment in new generation capacity and the share of each individual technology (determined on the basis of price and preference).<br /> <br /> ===Operational strategy===<br /> Use of power plants is based on operational costs, with low-cost technologies assumed to be used most often. This implies that capital-intensive plants with low operational costs, such as renewable and nuclear energy, operate as many hours as possible. To some degree, this is also true for other plants with low operational costs, such as coal. <br /> The operational decision is presented in the following three steps:<br /> #Renewable sources PV and wind are assigned, followed by hydropower, because these options have the lowest operational costs;<br /> #The peak load capacity (period of high electricity demand) is assigned on the basis of the operational costs of each available plant and the ability of these plants to provide peak load capacity; <br /> #Base load (period of medium to low energy demand) is assigned on the basis of the remaining capacity (after steps 1 and 2), operational costs and the ability of options to provide the base load capacity.<br /> <br /> <br /> ===Fossil-fuel and bio-energy power plants===<br /> A total of 20 types of power plants generating electricity using fossil fuels and bioenergy are included. These power plants represent different combinations of conventional technology, such as gasification and combined cycle (CC) technology; combined heat and power (CHP); and carbon capture and storage (CCS;(Hendriks et al., 2004b). The specific capital costs and thermal efficiencies of these types of plants are determined by exogenous assumptions that describe the technological progress of typical components of these plants:<br /> *For conventional power plants, the coal-fired plant is defined in terms of overall efficiency and investment cost. The characteristics of all other conventional plants (using oil, natural gas or bioenergy) are described in the investment differences for desulphurisation, fuel handling and efficiency.<br /> *For Combined Cycle (CC) power plants, the characteristics of a natural gas fired plant are set as the standard. Other CC plants (fuelled by oil, bioenergy and coal after gasification) are defined by indicating additional capital costs for gasification, efficiency losses due to gasification, and operation and maintenance (O&amp;M) costs for fuel handling. <br /> *Power plants with carbon-capture-and-storage systems (CCS) are assumed to be CC plants, but with fuel-specific lower efficiency and higher investment and O&amp;M costs (related to capture and storage). <br /> *The characteristics of combined-heat-and-power plants (CHP) are similar to those of other plants, but with an assumed small increase in capital costs, in combination with a lower efficiency for electric conversion and an added factor for heat efficiency. <br /> <br /> The cost of one unit electricity generated is equal to the sum of the capital cost, operational and maintenance costs (O&amp;M), fuel cost, and CO2 storage cost.<br /> <br /> ===Solar and wind power===<br /> <br /> The costs of solar and wind power in the model are determined by learning and depletion dynamics. For renewable energy, costs relate to capital, O&amp;M and system integration. The capital costs mostly relate to learning and depletion processes. Learning is represented by in learning curves (Box 4.1.3.1); depletion is by long-term in cost–supply curves. <br /> <br /> The additional system integration costs relate to curtailed electricity (if production exceeds demand and the overcapacity cannot be used within the system), backup capacity; and additional required spinning reserve. The last items are needed to avoid loss of power if the supply of wind or solar power drops suddenly, enabling a power scale up in a relatively short time, in power stations operating below maximum capacity ([[Hoogwijk, 2004]]).<br /> <br /> To determine curtailed electricity, the model compares 10 points on the load-demand curve at the overlap between demand and supply. For both wind and solar power, a typical load supply curve is assumed (see [[Hoogwijk, 2004]]). If supply exceeds demand, the overcapacity in electricity is assumed to be discarded, resulting in higher production costs.<br /> <br /> Because wind and solar power supply is intermittent (variable and thus not reliable), the model assumes that backup capacity needs to be installed. It is assumed that no backup is required for first 5% penetration of the intermittent capacity. However, for higher levels of penetration, the effective capacity (degree to which operators can rely on plants producing at a specific time) of intermittent resources is assumed to decrease. This is referred to as the capacity factor. This decrease leads to the need for backup power by low-cost options, such as gas turbines, the cost of which is allocated to the intermittent source.<br /> <br /> The required spinning reserve of the power system is the capacity that can be used to respond to a rapid increase in demand. This is assumed to be 3.5% of the installed capacity of a conventional power plant. If wind and solar power further penetrate the market, the model assumes an additional, required spinning reserve of 15% of the intermittent capacity (after subtraction of the 3.5% existing capacity). The related costs are allocated to the intermittent source.<br /> <br /> <br /> {{FormulaAndTableTemplate|Formula1_ED}}<br /> <br /> The costs of solar and wind power are the model determined by learning and depletion dynamics. For renewable energy, costs relate to capital, O&amp;M and system integration. The capital costs mostly relate to [[Energy conversion/Description/Technical learning|learning]] and depletion processes (learning is represented by so-called learning curves; depletion is represented by long-term cost–supply curves). <br /> <br /> The additional system integration costs relate to <br /> # Discarded electricity in cases where production exceeds demand and the overcapacity cannot be used within the system;<br /> # Back-up capacity;<br /> # Additional required spinning reserve;<br /> The two last items are needed to avoid loss of power if the supply of wind or solar power suddenly drops, enabling a power scale up in a relatively short time, in power stations operating below maximum capacity ([[Hoogwijk, 2004]]).<br /> *To determine discarded electricity, the model makes a comparison between 10 different points on the load-demand curve, at the overlap between demand and supply. For both wind and solar power, a typical load–supply curve is assumed (see [[Hoogwijk, 2004]]). If supply exceeds demand, the overcapacity in electricity is assumed to be discarded, resulting in higher production costs. <br /> *Because wind and solar power supply is intermittent (i.e. it varies and therefore is not reliable), the model assumes that so-called back-up capacity needs to be installed. For the first 5% penetration of the intermittent capacity, it is assumed that no-back is required. However, for higher levels of penetration, the effective capacity (i.e. degree to which operators can rely on plants producing at a particular moment in time) of intermittent resources is assumed to decrease (referred to as the capacity factor). This decrease leads to the need of back-up power(by low-cost options, such as gas turbines), the costs of which are allocated to the intermittent source.<br /> *The required spinning reserve of the power system (capacity that can be used to respond to a rapid increase in demand) is assumed to be 3.5% of the installed capacity of a conventional power plant. If wind and solar power further penetrate the market, the model assumes an additional, required spinning reserve of 15% of the intermittent capacity (but after first subtracting the 3.5% existing capacity). The related costs are allocated to the intermittent source.<br /> <br /> ==Nuclear power==<br /> For nuclear power, the costs also consists of capital, O&amp;M and nuclear fuel costs. Similar to the renewable energy options, technology improvement nuclear power is described via a learning curve (so costs decrease with cumulative installed capacity). At the same time, fuel costs increase as a function of depletion. Fuel costs are determined on the basis of the estimated extraction costs of uranium and thorium resources, as is described in the component [[Energy supply]]. A small trade model for these fission fuels is included.<br /> <br /> ==Hydrogen generation model==<br /> The structure of the hydrogen model is similar to that of the electric power model ([[Van Ruijven et al., 2007]]). There are, however, some important differences:<br /> *The hydrogen model distinguishes the following 11 supply options: hydrogen production plants on the basis of coal, oil, natural gas and bio-energy, with and <br /> without carbon capture and storage (8 plants), hydrogen production from electrolysis, direct hydrogen production from solar thermal processes, and, finally, small methane reform plants. <br /> *For simplification, no description of preferences for different power plants is accounted for in the operational strategy. In other words, the load factor for each option equals the total production divided by the capacity for each region.<br /> *Intermittence does not play an important role, as hydrogen can be stored to some degree. Therefore, there are no equations simulating system integration.<br /> *Hydrogen can be traded. Therefore, a trade model is added, similar to the trade models for fossil fuels, as is described in the [[Energy supply]] section.<br /> <br /> &lt;references/&gt;</div>

JoeriOostenrijk https://models.pbl.nl/index.php?title=Energy_conversion/Description&diff=21519 2014-05-08T16:29:05Z

<p>JoeriOostenrijk: </p> <hr /> <div>{{ComponentDescriptionTemplate<br /> |Reference=Hoogwijk, 2004; Van Vuuren, 2007; Hendriks et al., 2004b; Van Ruijven et al., 2007;<br /> |Description=[[TIMER model|TIMER]] includes two main energy conversion modules: Electric power generation and hydrogen generation. Below, electric power generation is described in detail. In addition, the key characteristics of the hydrogen generation model, which follows a similar structure, are presented.<br /> <br /> ==Electric power generation==<br /> As shown in the flowchart, two key elements of the electric power generation are the investment strategy and the operational strategy in the sector. A challenge in simulating electricity production in an aggregated model is that in reality electricity production depends on a range of complex factors, related to costs, reliance, and the time required to switch on technologies. Modelling these factors requires a high level of detail and thus {{AbbrTemplate|IAM}}s) such as [[TIMER model|TIMER]] concentrate on introducing a set of simplified, meta relationships ([[Hoogwijk, 2004]]; [[Van Vuuren, 2007]]).<br /> <br /> ===Total demand for new capacity===<br /> The electricity capacity required to meet the demand per region is based on a forecast of the maximum electricity demand plus a reserve margin of about 10% (including the capacity credit assigned to different forms of electricity generation). Maximum demand is calculated on the basis of an assumed monthly shape of the load duration curve (LDC) and the gross electricity demand. The latter comprises the net electricity demand from the end-use sectors plus electricity trade and transmission losses ({{AbbrTemplate|LDC}}) accounts for characteristics such as cooling and lighting demand). The demand for new generation capacity is the difference between the required and existing capacity. Power plants are assumed to be replaced at the end of their lifetime, which varies from 30 to 50 years, depending on the technology and is currently fixed in the model.<br /> <br /> ===Decisions to invest in specific options ===<br /> In the following step, a decision is made to invest in different generation technologies. In the model, this is done on the basis of the price of electricity (in USD/kWhe) produced per technology, using a multinomial logit equation that assigns larger market shares to the lower cost options. The specific costs of each option is broken down into a number of categories: investment or capital costs (USD/kWe), fuel costs (USD/GJ), operational and maintenance costs (OM) and other costs (see further). An exception is hydropower capacity, which is exogenously prescribed, because large hydropower plants often have functions other than only electricity production (e.g. water supply and flood control). In the equations, some constraints are added to account for limitations in supply (e.g. restrictions on biomass availability). The investments needed for each option are given in the form of total investment in new generation capacity and the share of each individual technology (determined on the basis of price and preference).<br /> <br /> ===Operational strategy===<br /> Use of power plants is based on operational costs, with low-cost technologies assumed to be used most often. This implies that capital-intensive plants with low operational costs, such as renewable and nuclear energy, operate as many hours as possible. To some degree, this is also true for other plants with low operational costs, such as coal. <br /> The operational decision is presented in the following three steps:<br /> #Renewable sources PV and wind are assigned, followed by hydropower, because these options have the lowest operational costs;<br /> #The peak load capacity (period of high electricity demand) is assigned on the basis of the operational costs of each available plant and the ability of these plants to provide peak load capacity; <br /> #Base load (period of medium to low energy demand) is assigned on the basis of the remaining capacity (after steps 1 and 2), operational costs and the ability of options to provide the base load capacity.<br /> <br /> <br /> ===Fossil-fuel and bio-energy power plants===<br /> A total of 20 types of power plants generating electricity using fossil fuels and bioenergy are included. These power plants represent different combinations of conventional technology, such as gasification and combined cycle (CC) technology; combined heat and power (CHP); and carbon capture and storage ([[CCS]];([[Hendriks et al., 2004b]]). The specific capital costs and thermal efficiencies of these types of plants are determined by exogenous assumptions that describe the technological progress of typical components of these plants:<br /> *For conventional power plants, the coal-fired plant is defined in terms of overall efficiency and investment cost. The characteristics of all other conventional plants (using oil, natural gas or bioenergy) are described in the investment differences for desulphurisation, fuel handling and efficiency.<br /> *For Combined Cycle (CC) power plants, the characteristics of a natural gas fired plant are set as the standard. Other CC plants (fuelled by oil, bioenergy and coal after gasification) are defined by indicating additional capital costs for gasification, efficiency losses due to gasification, and operation and maintenance (O&amp;M) costs for fuel handling. <br /> *Power plants with carbon-capture-and-storage systems (CCS) are assumed to be CC plants, but with fuel-specific lower efficiency and higher investment and O&amp;M costs (related to capture and storage). <br /> *The characteristics of combined-heat-and-power plants (CHP) are similar to those of other plants, but with an assumed small increase in capital costs, in combination with a lower efficiency for electric conversion and an added factor for heat efficiency. <br /> <br /> The cost of one unit electricity generated is equal to the sum of the capital cost, operational and maintenance costs (O&amp;M), fuel cost, and CO2 storage cost.<br /> <br /> ===Solar and wind power===<br /> <br /> The costs of solar and wind power in the model are determined by learning and depletion dynamics. For renewable energy, costs relate to capital, O&amp;M and system integration. The capital costs mostly relate to learning and depletion processes. Learning is represented by in learning curves (Box 4.1.3.1); depletion is by long-term in cost–supply curves. <br /> <br /> The additional system integration costs relate to curtailed electricity (if production exceeds demand and the overcapacity cannot be used within the system), backup capacity; and additional required spinning reserve. The last items are needed to avoid loss of power if the supply of wind or solar power drops suddenly, enabling a power scale up in a relatively short time, in power stations operating below maximum capacity ([[Hoogwijk, 2004]]).<br /> <br /> To determine curtailed electricity, the model compares 10 points on the load-demand curve at the overlap between demand and supply. For both wind and solar power, a typical load supply curve is assumed (see [[Hoogwijk, 2004]]). If supply exceeds demand, the overcapacity in electricity is assumed to be discarded, resulting in higher production costs.<br /> <br /> Because wind and solar power supply is intermittent (variable and thus not reliable), the model assumes that backup capacity needs to be installed. It is assumed that no backup is required for first 5% penetration of the intermittent capacity. However, for higher levels of penetration, the effective capacity (degree to which operators can rely on plants producing at a specific time) of intermittent resources is assumed to decrease. This is referred to as the capacity factor. This decrease leads to the need for backup power by low-cost options, such as gas turbines, the cost of which is allocated to the intermittent source.<br /> <br /> The required spinning reserve of the power system is the capacity that can be used to respond to a rapid increase in demand. This is assumed to be 3.5% of the installed capacity of a conventional power plant. If wind and solar power further penetrate the market, the model assumes an additional, required spinning reserve of 15% of the intermittent capacity (after subtraction of the 3.5% existing capacity). The related costs are allocated to the intermittent source.<br /> <br /> {{FormulaAndTableTemplate|Formula1_ED}}<br /> <br /> ==Nuclear power==<br /> The costs of nuclear power also include capital, O&amp;M and nuclear fuel costs. Similar to the renewable energy options, technology improvement in nuclear power is described via a learning curve (costs decrease with cumulative installed capacity). Fuel costs increase as a function of depletion. Fuel costs are determined on the basis of the estimated extraction costs for uranium and thorium resources, see [[Energy Supply]]. A small trade model for these fission fuels is included..<br /> <br /> ==Hydrogen generation model==<br /> The structure of the hydrogen generation submodule is similar to that for electric power generation ([[Van Ruijven et al., 2007]]) but with following differences:<br /> *There are only eleven supply options for hydrogen production coal, oil, natural gas and bioenergy, with and without carbon capture and storage (8 plants); hydrogen production from electrolysis, direct hydrogen production from solar thermal processes; and small methane reform plants. <br /> *No description of preferences for different power plants is taken into account in the operational strategy. The load factor for each option equals the total production divided by the capacity for each region.<br /> *Intermittence does not play an important role because hydrogen can be stored to some degree. Thus, there are no equations simulating system integration.<br /> *Hydrogen can be traded. A trade model is added, similar to those for fossil fuels described in * [[Energy Supply]].<br /> <br /> &lt;references/&gt;<br /> }}<br /> <br /> }}<br /> s such as [[TIMER model|TIMER]] concentrate on introducing a set of simplified, meta relationships ([[Hoogwijk, 2004]]; [[Van Vuuren, 2007]]).<br /> <br /> ===Total demand for new capacity===<br /> The electricity capacity required to meet the demand per region is based on a forecast of the maximum electricity demand plus a reserve margin of about 10% (including the capacity credit assigned to different forms of electricity generation). Maximum demand is calculated on the basis of an assumed monthly shape of the load duration curve (LDC) and the gross electricity demand. The latter comprises the net electricity demand from the end-use sectors plus electricity trade and transmission losses ({{AbbrTemplate|LDC}}) accounts for characteristics such as cooling and lighting demand). The demand for new generation capacity is the difference between the required and existing capacity. Power plants are assumed to be replaced at the end of their lifetime, which varies from 30 to 50 years, depending on the technology and is currently fixed in the model.<br /> <br /> ===Decisions to invest in specific options ===<br /> In the following step, a decision is made to invest in different generation technologies. In the model, this is done on the basis of the price of electricity (in {{AbbrTemplate|USD/kWhe}} produced per technology, using a multinomial logit equation that assigns larger market shares to the lower cost options. The specific costs of each option is broken down into a number of categories: investment or capital costs (USD/kWe), fuel costs ([[HasAcronym::USD/GJ]]), operational and maintenance costs (OM) and other costs (see further). An exception is hydropower capacity, which is exogenously prescribed, because large hydropower plants often have functions other than only electricity production (e.g. water supply and flood control). In the equations, some constraints are added to account for limitations in supply (e.g. restrictions on biomass availability). The investments needed for each option are given in the form of total investment in new generation capacity and the share of each individual technology (determined on the basis of price and preference).<br /> <br /> ===Operational strategy===<br /> Use of power plants is based on operational costs, with low-cost technologies assumed to be used most often. This implies that capital-intensive plants with low operational costs, such as renewable and nuclear energy, operate as many hours as possible. To some degree, this is also true for other plants with low operational costs, such as coal. <br /> The operational decision is presented in the following three steps:<br /> #Renewable sources PV and wind are assigned, followed by hydropower, because these options have the lowest operational costs;<br /> #The peak load capacity (period of high electricity demand) is assigned on the basis of the operational costs of each available plant and the ability of these plants to provide peak load capacity; <br /> #Base load (period of medium to low energy demand) is assigned on the basis of the remaining capacity (after steps 1 and 2), operational costs and the ability of options to provide the base load capacity.<br /> <br /> <br /> ===Fossil-fuel and bio-energy power plants===<br /> A total of 20 types of power plants generating electricity using fossil fuels and bioenergy are included. These power plants represent different combinations of conventional technology, such as gasification and combined cycle (CC) technology; combined heat and power (CHP); and carbon capture and storage (CCS;(Hendriks et al., 2004b). The specific capital costs and thermal efficiencies of these types of plants are determined by exogenous assumptions that describe the technological progress of typical components of these plants:<br /> *For conventional power plants, the coal-fired plant is defined in terms of overall efficiency and investment cost. The characteristics of all other conventional plants (using oil, natural gas or bioenergy) are described in the investment differences for desulphurisation, fuel handling and efficiency.<br /> *For Combined Cycle (CC) power plants, the characteristics of a natural gas fired plant are set as the standard. Other CC plants (fuelled by oil, bioenergy and coal after gasification) are defined by indicating additional capital costs for gasification, efficiency losses due to gasification, and operation and maintenance (O&amp;M) costs for fuel handling. <br /> *Power plants with carbon-capture-and-storage systems (CCS) are assumed to be CC plants, but with fuel-specific lower efficiency and higher investment and O&amp;M costs (related to capture and storage). <br /> *The characteristics of combined-heat-and-power plants (CHP) are similar to those of other plants, but with an assumed small increase in capital costs, in combination with a lower efficiency for electric conversion and an added factor for heat efficiency. <br /> <br /> The cost of one unit electricity generated is equal to the sum of the capital cost, operational and maintenance costs (O&amp;M), fuel cost, and CO2 storage cost.<br /> <br /> ===Solar and wind power===<br /> <br /> The costs of solar and wind power in the model are determined by learning and depletion dynamics. For renewable energy, costs relate to capital, O&amp;M and system integration. The capital costs mostly relate to learning and depletion processes. Learning is represented by in learning curves (Box 4.1.3.1); depletion is by long-term in cost–supply curves. <br /> <br /> The additional system integration costs relate to curtailed electricity (if production exceeds demand and the overcapacity cannot be used within the system), backup capacity; and additional required spinning reserve. The last items are needed to avoid loss of power if the supply of wind or solar power drops suddenly, enabling a power scale up in a relatively short time, in power stations operating below maximum capacity ([[Hoogwijk, 2004]]).<br /> <br /> To determine curtailed electricity, the model compares 10 points on the load-demand curve at the overlap between demand and supply. For both wind and solar power, a typical load supply curve is assumed (see [[Hoogwijk, 2004]]). If supply exceeds demand, the overcapacity in electricity is assumed to be discarded, resulting in higher production costs.<br /> <br /> Because wind and solar power supply is intermittent (variable and thus not reliable), the model assumes that backup capacity needs to be installed. It is assumed that no backup is required for first 5% penetration of the intermittent capacity. However, for higher levels of penetration, the effective capacity (degree to which operators can rely on plants producing at a specific time) of intermittent resources is assumed to decrease. This is referred to as the capacity factor. This decrease leads to the need for backup power by low-cost options, such as gas turbines, the cost of which is allocated to the intermittent source.<br /> <br /> The required spinning reserve of the power system is the capacity that can be used to respond to a rapid increase in demand. This is assumed to be 3.5% of the installed capacity of a conventional power plant. If wind and solar power further penetrate the market, the model assumes an additional, required spinning reserve of 15% of the intermittent capacity (after subtraction of the 3.5% existing capacity). The related costs are allocated to the intermittent source.<br /> <br /> <br /> {{FormulaAndTableTemplate|Formula1_ED}}<br /> <br /> The costs of solar and wind power are the model determined by learning and depletion dynamics. For renewable energy, costs relate to capital, O&amp;M and system integration. The capital costs mostly relate to [[Energy conversion/Description/Technical learning|learning]] and depletion processes (learning is represented by so-called learning curves; depletion is represented by long-term cost–supply curves). <br /> <br /> The additional system integration costs relate to <br /> # Discarded electricity in cases where production exceeds demand and the overcapacity cannot be used within the system;<br /> # Back-up capacity;<br /> # Additional required spinning reserve;<br /> The two last items are needed to avoid loss of power if the supply of wind or solar power suddenly drops, enabling a power scale up in a relatively short time, in power stations operating below maximum capacity ([[Hoogwijk, 2004]]).<br /> *To determine discarded electricity, the model makes a comparison between 10 different points on the load-demand curve, at the overlap between demand and supply. For both wind and solar power, a typical load–supply curve is assumed (see [[Hoogwijk, 2004]]). If supply exceeds demand, the overcapacity in electricity is assumed to be discarded, resulting in higher production costs. <br /> *Because wind and solar power supply is intermittent (i.e. it varies and therefore is not reliable), the model assumes that so-called back-up capacity needs to be installed. For the first 5% penetration of the intermittent capacity, it is assumed that no-back is required. However, for higher levels of penetration, the effective capacity (i.e. degree to which operators can rely on plants producing at a particular moment in time) of intermittent resources is assumed to decrease (referred to as the capacity factor). This decrease leads to the need of back-up power(by low-cost options, such as gas turbines), the costs of which are allocated to the intermittent source.<br /> *The required spinning reserve of the power system (capacity that can be used to respond to a rapid increase in demand) is assumed to be 3.5% of the installed capacity of a conventional power plant. If wind and solar power further penetrate the market, the model assumes an additional, required spinning reserve of 15% of the intermittent capacity (but after first subtracting the 3.5% existing capacity). The related costs are allocated to the intermittent source.<br /> <br /> ==Nuclear power==<br /> For nuclear power, the costs also consists of capital, O&amp;M and nuclear fuel costs. Similar to the renewable energy options, technology improvement nuclear power is described via a learning curve (so costs decrease with cumulative installed capacity). At the same time, fuel costs increase as a function of depletion. Fuel costs are determined on the basis of the estimated extraction costs of uranium and thorium resources, as is described in the component [[Energy supply]]. A small trade model for these fission fuels is included.<br /> <br /> ==Hydrogen generation model==<br /> The structure of the hydrogen model is similar to that of the electric power model ([[Van Ruijven et al., 2007]]). There are, however, some important differences:<br /> *The hydrogen model distinguishes the following 11 supply options: hydrogen production plants on the basis of coal, oil, natural gas and bio-energy, with and <br /> without carbon capture and storage (8 plants), hydrogen production from electrolysis, direct hydrogen production from solar thermal processes, and, finally, small methane reform plants. <br /> *For simplification, no description of preferences for different power plants is accounted for in the operational strategy. In other words, the load factor for each option equals the total production divided by the capacity for each region.<br /> *Intermittence does not play an important role, as hydrogen can be stored to some degree. Therefore, there are no equations simulating system integration.<br /> *Hydrogen can be traded. Therefore, a trade model is added, similar to the trade models for fossil fuels, as is described in the [[Energy supply]] section.<br /> <br /> &lt;references/&gt;</div>

JoeriOostenrijk https://models.pbl.nl/index.php?title=Energy_conversion/Description&diff=21518 2014-05-08T16:27:00Z

<p>JoeriOostenrijk: </p> <hr /> <div>{{ComponentDescriptionTemplate<br /> |Reference=Hoogwijk, 2004; Van Vuuren, 2007; Hendriks et al., 2004b; Van Ruijven et al., 2007;<br /> |Description=[[TIMER model|TIMER]] includes two main energy conversion modules: Electric power generation and hydrogen generation. Below, electric power generation is described in detail. In addition, the key characteristics of the hydrogen generation model, which follows a similar structure, are presented.<br /> <br /> ==Electric power generation==<br /> As shown in the flowchart, two key elements of the electric power generation are the investment strategy and the operational strategy in the sector. A challenge in simulating electricity production in an aggregated model is that in reality electricity production depends on a range of complex factors, related to costs, reliance, and the time required to switch on technologies. Modelling these factors requires a high level of detail and thus {{AbbrTemplate|IAM}}s) such as [[TIMER model|TIMER]] concentrate on introducing a set of simplified, meta relationships ([[Hoogwijk, 2004]]; [[Van Vuuren, 2007]]).<br /> <br /> ===Total demand for new capacity===<br /> The electricity capacity required to meet the demand per region is based on a forecast of the maximum electricity demand plus a reserve margin of about 10% (including the capacity credit assigned to different forms of electricity generation). Maximum demand is calculated on the basis of an assumed monthly shape of the load duration curve (LDC) and the gross electricity demand. The latter comprises the net electricity demand from the end-use sectors plus electricity trade and transmission losses ({{AbbrTemplate|LDC}}) accounts for characteristics such as cooling and lighting demand). The demand for new generation capacity is the difference between the required and existing capacity. Power plants are assumed to be replaced at the end of their lifetime, which varies from 30 to 50 years, depending on the technology and is currently fixed in the model.<br /> <br /> ===Decisions to invest in specific options ===<br /> In the following step, a decision is made to invest in different generation technologies. In the model, this is done on the basis of the price of electricity (in USD/kWhe) produced per technology, using a multinomial logit equation that assigns larger market shares to the lower cost options. The specific costs of each option is broken down into a number of categories: investment or capital costs (USD/kWe), fuel costs (USD/GJ), operational and maintenance costs (OM) and other costs (see further). An exception is hydropower capacity, which is exogenously prescribed, because large hydropower plants often have functions other than only electricity production (e.g. water supply and flood control). In the equations, some constraints are added to account for limitations in supply (e.g. restrictions on biomass availability). The investments needed for each option are given in the form of total investment in new generation capacity and the share of each individual technology (determined on the basis of price and preference).<br /> <br /> ===Operational strategy===<br /> Use of power plants is based on operational costs, with low-cost technologies assumed to be used most often. This implies that capital-intensive plants with low operational costs, such as renewable and nuclear energy, operate as many hours as possible. To some degree, this is also true for other plants with low operational costs, such as coal. <br /> The operational decision is presented in the following three steps:<br /> #Renewable sources PV and wind are assigned, followed by hydropower, because these options have the lowest operational costs;<br /> #The peak load capacity (period of high electricity demand) is assigned on the basis of the operational costs of each available plant and the ability of these plants to provide peak load capacity; <br /> #Base load (period of medium to low energy demand) is assigned on the basis of the remaining capacity (after steps 1 and 2), operational costs and the ability of options to provide the base load capacity.<br /> <br /> <br /> ===Fossil-fuel and bio-energy power plants===<br /> A total of 20 types of power plants generating electricity using fossil fuels and bioenergy are included. These power plants represent different combinations of conventional technology, such as gasification and combined cycle (CC) technology; combined heat and power (CHP); and carbon capture and storage ([[CCS]];([[Hendriks et al., 2004b]]). The specific capital costs and thermal efficiencies of these types of plants are determined by exogenous assumptions that describe the technological progress of typical components of these plants:<br /> *For conventional power plants, the coal-fired plant is defined in terms of overall efficiency and investment cost. The characteristics of all other conventional plants (using oil, natural gas or bioenergy) are described in the investment differences for desulphurisation, fuel handling and efficiency.<br /> *For Combined Cycle (CC) power plants, the characteristics of a natural gas fired plant are set as the standard. Other CC plants (fuelled by oil, bioenergy and coal after gasification) are defined by indicating additional capital costs for gasification, efficiency losses due to gasification, and operation and maintenance (O&amp;M) costs for fuel handling. <br /> *Power plants with carbon-capture-and-storage systems (CCS) are assumed to be CC plants, but with fuel-specific lower efficiency and higher investment and O&amp;M costs (related to capture and storage). <br /> *The characteristics of combined-heat-and-power plants (CHP) are similar to those of other plants, but with an assumed small increase in capital costs, in combination with a lower efficiency for electric conversion and an added factor for heat efficiency. <br /> <br /> The cost of one unit electricity generated is equal to the sum of the capital cost, operational and maintenance costs (O&amp;M), fuel cost, and CO2 storage cost.<br /> <br /> ===Solar and wind power===<br /> <br /> The costs of solar and wind power in the model are determined by learning and depletion dynamics. For renewable energy, costs relate to capital, O&amp;M and system integration. The capital costs mostly relate to learning and depletion processes. Learning is represented by in learning curves (Box 4.1.3.1); depletion is by long-term in cost–supply curves. <br /> <br /> The additional system integration costs relate to curtailed electricity (if production exceeds demand and the overcapacity cannot be used within the system), backup capacity; and additional required spinning reserve. The last items are needed to avoid loss of power if the supply of wind or solar power drops suddenly, enabling a power scale up in a relatively short time, in power stations operating below maximum capacity ([[Hoogwijk, 2004]]).<br /> <br /> To determine curtailed electricity, the model compares 10 points on the load-demand curve at the overlap between demand and supply. For both wind and solar power, a typical load supply curve is assumed (see [[Hoogwijk, 2004]]). If supply exceeds demand, the overcapacity in electricity is assumed to be discarded, resulting in higher production costs.<br /> <br /> Because wind and solar power supply is intermittent (variable and thus not reliable), the model assumes that backup capacity needs to be installed. It is assumed that no backup is required for first 5% penetration of the intermittent capacity. However, for higher levels of penetration, the effective capacity (degree to which operators can rely on plants producing at a specific time) of intermittent resources is assumed to decrease. This is referred to as the capacity factor. This decrease leads to the need for backup power by low-cost options, such as gas turbines, the cost of which is allocated to the intermittent source.<br /> <br /> The required spinning reserve of the power system is the capacity that can be used to respond to a rapid increase in demand. This is assumed to be 3.5% of the installed capacity of a conventional power plant. If wind and solar power further penetrate the market, the model assumes an additional, required spinning reserve of 15% of the intermittent capacity (after subtraction of the 3.5% existing capacity). The related costs are allocated to the intermittent source.<br /> <br /> {{FormulaAndTableTemplate|Formula1_ED}}<br /> <br /> ==Nuclear power==<br /> The costs of nuclear power also include capital, O&amp;M and nuclear fuel costs. Similar to the renewable energy options, technology improvement in nuclear power is described via a learning curve (costs decrease with cumulative installed capacity). Fuel costs increase as a function of depletion. Fuel costs are determined on the basis of the estimated extraction costs for uranium and thorium resources, see [[Energy Supply]]. A small trade model for these fission fuels is included..<br /> <br /> ==Hydrogen generation model==<br /> The structure of the hydrogen generation submodule is similar to that for electric power generation ([[Van Ruijven et al., 2007]]) but with following differences:<br /> *There are only eleven supply options for hydrogen production coal, oil, natural gas and bioenergy, with and without carbon capture and storage (8 plants); hydrogen production from electrolysis, direct hydrogen production from solar thermal processes; and small methane reform plants. <br /> *No description of preferences for different power plants is taken into account in the operational strategy. The load factor for each option equals the total production divided by the capacity for each region.<br /> *Intermittence does not play an important role because hydrogen can be stored to some degree. Thus, there are no equations simulating system integration.<br /> *Hydrogen can be traded. A trade model is added, similar to those for fossil fuels described in * [[Energy Supply]].<br /> }}<br /> s such as [[TIMER model|TIMER]] concentrate on introducing a set of simplified, meta relationships ([[Hoogwijk, 2004]]; [[Van Vuuren, 2007]]).<br /> <br /> ===Total demand for new capacity===<br /> The electricity capacity required to meet the demand per region is based on a forecast of the maximum electricity demand plus a reserve margin of about 10% (including the capacity credit assigned to different forms of electricity generation). Maximum demand is calculated on the basis of an assumed monthly shape of the load duration curve (LDC) and the gross electricity demand. The latter comprises the net electricity demand from the end-use sectors plus electricity trade and transmission losses ({{AbbrTemplate|LDC}}) accounts for characteristics such as cooling and lighting demand). The demand for new generation capacity is the difference between the required and existing capacity. Power plants are assumed to be replaced at the end of their lifetime, which varies from 30 to 50 years, depending on the technology and is currently fixed in the model.<br /> <br /> ===Decisions to invest in specific options ===<br /> In the following step, a decision is made to invest in different generation technologies. In the model, this is done on the basis of the price of electricity (in {{AbbrTemplate|USD/kWhe}} produced per technology, using a multinomial logit equation that assigns larger market shares to the lower cost options. The specific costs of each option is broken down into a number of categories: investment or capital costs (USD/kWe), fuel costs ([[HasAcronym::USD/GJ]]), operational and maintenance costs (OM) and other costs (see further). An exception is hydropower capacity, which is exogenously prescribed, because large hydropower plants often have functions other than only electricity production (e.g. water supply and flood control). In the equations, some constraints are added to account for limitations in supply (e.g. restrictions on biomass availability). The investments needed for each option are given in the form of total investment in new generation capacity and the share of each individual technology (determined on the basis of price and preference).<br /> <br /> ===Operational strategy===<br /> Use of power plants is based on operational costs, with low-cost technologies assumed to be used most often. This implies that capital-intensive plants with low operational costs, such as renewable and nuclear energy, operate as many hours as possible. To some degree, this is also true for other plants with low operational costs, such as coal. <br /> The operational decision is presented in the following three steps:<br /> #Renewable sources PV and wind are assigned, followed by hydropower, because these options have the lowest operational costs;<br /> #The peak load capacity (period of high electricity demand) is assigned on the basis of the operational costs of each available plant and the ability of these plants to provide peak load capacity; <br /> #Base load (period of medium to low energy demand) is assigned on the basis of the remaining capacity (after steps 1 and 2), operational costs and the ability of options to provide the base load capacity.<br /> <br /> <br /> ===Fossil-fuel and bio-energy power plants===<br /> A total of 20 types of power plants generating electricity using fossil fuels and bioenergy are included. These power plants represent different combinations of conventional technology, such as gasification and combined cycle (CC) technology; combined heat and power (CHP); and carbon capture and storage (CCS;(Hendriks et al., 2004b). The specific capital costs and thermal efficiencies of these types of plants are determined by exogenous assumptions that describe the technological progress of typical components of these plants:<br /> *For conventional power plants, the coal-fired plant is defined in terms of overall efficiency and investment cost. The characteristics of all other conventional plants (using oil, natural gas or bioenergy) are described in the investment differences for desulphurisation, fuel handling and efficiency.<br /> *For Combined Cycle (CC) power plants, the characteristics of a natural gas fired plant are set as the standard. Other CC plants (fuelled by oil, bioenergy and coal after gasification) are defined by indicating additional capital costs for gasification, efficiency losses due to gasification, and operation and maintenance (O&amp;M) costs for fuel handling. <br /> *Power plants with carbon-capture-and-storage systems (CCS) are assumed to be CC plants, but with fuel-specific lower efficiency and higher investment and O&amp;M costs (related to capture and storage). <br /> *The characteristics of combined-heat-and-power plants (CHP) are similar to those of other plants, but with an assumed small increase in capital costs, in combination with a lower efficiency for electric conversion and an added factor for heat efficiency. <br /> <br /> The cost of one unit electricity generated is equal to the sum of the capital cost, operational and maintenance costs (O&amp;M), fuel cost, and CO2 storage cost.<br /> <br /> ===Solar and wind power===<br /> <br /> The costs of solar and wind power in the model are determined by learning and depletion dynamics. For renewable energy, costs relate to capital, O&amp;M and system integration. The capital costs mostly relate to learning and depletion processes. Learning is represented by in learning curves (Box 4.1.3.1); depletion is by long-term in cost–supply curves. <br /> <br /> The additional system integration costs relate to curtailed electricity (if production exceeds demand and the overcapacity cannot be used within the system), backup capacity; and additional required spinning reserve. The last items are needed to avoid loss of power if the supply of wind or solar power drops suddenly, enabling a power scale up in a relatively short time, in power stations operating below maximum capacity ([[Hoogwijk, 2004]]).<br /> <br /> To determine curtailed electricity, the model compares 10 points on the load-demand curve at the overlap between demand and supply. For both wind and solar power, a typical load supply curve is assumed (see [[Hoogwijk, 2004]]). If supply exceeds demand, the overcapacity in electricity is assumed to be discarded, resulting in higher production costs.<br /> <br /> Because wind and solar power supply is intermittent (variable and thus not reliable), the model assumes that backup capacity needs to be installed. It is assumed that no backup is required for first 5% penetration of the intermittent capacity. However, for higher levels of penetration, the effective capacity (degree to which operators can rely on plants producing at a specific time) of intermittent resources is assumed to decrease. This is referred to as the capacity factor. This decrease leads to the need for backup power by low-cost options, such as gas turbines, the cost of which is allocated to the intermittent source.<br /> <br /> The required spinning reserve of the power system is the capacity that can be used to respond to a rapid increase in demand. This is assumed to be 3.5% of the installed capacity of a conventional power plant. If wind and solar power further penetrate the market, the model assumes an additional, required spinning reserve of 15% of the intermittent capacity (after subtraction of the 3.5% existing capacity). The related costs are allocated to the intermittent source.<br /> <br /> <br /> {{FormulaAndTableTemplate|Formula1_ED}}<br /> <br /> The costs of solar and wind power are the model determined by learning and depletion dynamics. For renewable energy, costs relate to capital, O&amp;M and system integration. The capital costs mostly relate to [[Energy conversion/Description/Technical learning|learning]] and depletion processes (learning is represented by so-called learning curves; depletion is represented by long-term cost–supply curves). <br /> <br /> The additional system integration costs relate to <br /> # Discarded electricity in cases where production exceeds demand and the overcapacity cannot be used within the system;<br /> # Back-up capacity;<br /> # Additional required spinning reserve;<br /> The two last items are needed to avoid loss of power if the supply of wind or solar power suddenly drops, enabling a power scale up in a relatively short time, in power stations operating below maximum capacity ([[Hoogwijk, 2004]]).<br /> *To determine discarded electricity, the model makes a comparison between 10 different points on the load-demand curve, at the overlap between demand and supply. For both wind and solar power, a typical load–supply curve is assumed (see [[Hoogwijk, 2004]]). If supply exceeds demand, the overcapacity in electricity is assumed to be discarded, resulting in higher production costs. <br /> *Because wind and solar power supply is intermittent (i.e. it varies and therefore is not reliable), the model assumes that so-called back-up capacity needs to be installed. For the first 5% penetration of the intermittent capacity, it is assumed that no-back is required. However, for higher levels of penetration, the effective capacity (i.e. degree to which operators can rely on plants producing at a particular moment in time) of intermittent resources is assumed to decrease (referred to as the capacity factor). This decrease leads to the need of back-up power(by low-cost options, such as gas turbines), the costs of which are allocated to the intermittent source.<br /> *The required spinning reserve of the power system (capacity that can be used to respond to a rapid increase in demand) is assumed to be 3.5% of the installed capacity of a conventional power plant. If wind and solar power further penetrate the market, the model assumes an additional, required spinning reserve of 15% of the intermittent capacity (but after first subtracting the 3.5% existing capacity). The related costs are allocated to the intermittent source.<br /> <br /> ==Nuclear power==<br /> For nuclear power, the costs also consists of capital, O&amp;M and nuclear fuel costs. Similar to the renewable energy options, technology improvement nuclear power is described via a learning curve (so costs decrease with cumulative installed capacity). At the same time, fuel costs increase as a function of depletion. Fuel costs are determined on the basis of the estimated extraction costs of uranium and thorium resources, as is described in the component [[Energy supply]]. A small trade model for these fission fuels is included.<br /> <br /> ==Hydrogen generation model==<br /> The structure of the hydrogen model is similar to that of the electric power model ([[Van Ruijven et al., 2007]]). There are, however, some important differences:<br /> *The hydrogen model distinguishes the following 11 supply options: hydrogen production plants on the basis of coal, oil, natural gas and bio-energy, with and <br /> without carbon capture and storage (8 plants), hydrogen production from electrolysis, direct hydrogen production from solar thermal processes, and, finally, small methane reform plants. <br /> *For simplification, no description of preferences for different power plants is accounted for in the operational strategy. In other words, the load factor for each option equals the total production divided by the capacity for each region.<br /> *Intermittence does not play an important role, as hydrogen can be stored to some degree. Therefore, there are no equations simulating system integration.<br /> *Hydrogen can be traded. Therefore, a trade model is added, similar to the trade models for fossil fuels, as is described in the [[Energy supply]] section.<br /> <br /> &lt;references/&gt;</div>

JoeriOostenrijk https://models.pbl.nl/index.php?title=Energy_conversion/Policy_issues&diff=21517 2014-05-08T16:22:16Z

<p>JoeriOostenrijk: </p> <hr /> <div>{{ComponentPolicyIssueTemplate<br /> |Reference=Kruyt et al., 2009; PBL, 2012;<br /> |Description=The conversion model may be used to generate scenarios with and without climate policy. The results according to a typical baseline scenario are shown in the figure below. At the moment, coal is by far the most important feedstock for power generation, globally speaking. In high-income regions, the contribution of coal faces competition from natural gas. In emerging economies, such as those of China and India, however, coal is still by far the largest resource used. The baseline scenario projects coal use to expand in the future. The underlying reasons for this expansion are the fast increase in electricity use in these emerging economies, and the stronger price increases for natural gas than for coal. At the same time, wind power and biomass-fired power plants rapidly expand their total capacity, on a global scale.<br /> |Example=Model analyses show that a high proportion of emission reductions would be achieved through supply side changes.The figure below shows the capacity for different supply side options under the baseline scenario and various pathways consistent with the 2 &lt;sup&gt;o&lt;/sup&gt;C climate change target. Although the share of unabated fossil-fuel use is still 80% of total primary energy under the baseline scenario (see above), by 2050 this would need to be around 15% to 20% according to the 2 &lt;sup&gt;o&lt;/sup&gt;C scenarios. The results show that pathways can be identified in which the remaining energy comes from bio-energy, other renewable energy, nuclear energy, and from fossil-fuel energy combined with {{AbbrTemplate|CSS}}. There is flexibility in the choice of these options, as illustrated here in the Decentralised Solutions and Global Technology pathways with very different patterns for nuclear power and renewable energy. In the IMAGE model, however, under nearly all scenarios, the combination of bio-energy and CCS, and CCS in general, plays a critical role in achieving the 2 &lt;sup&gt;o&lt;/sup&gt;C target ([[PBL, 2012]]).<br /> }}</div>

JoeriOostenrijk https://models.pbl.nl/index.php?title=Energy_conversion/Description&diff=21516 2014-05-08T16:18:34Z

<p>JoeriOostenrijk: </p> <hr /> <div>{{ComponentDescriptionTemplate<br /> |Reference=Hoogwijk, 2004; Van Vuuren, 2007; Hendriks et al., 2004b; Van Ruijven et al., 2007;<br /> |Description=[[TIMER model|TIMER]] includes two main energy conversion modules: Electric power generation and hydrogen generation. Below, electric power generation is described in detail. In addition, the key characteristics of the hydrogen generation model, which follows a similar structure, are presented.<br /> <br /> ==Electric power generation==<br /> As shown in the flowchart, two key elements of the electric power generation are the investment strategy and the operational strategy in the sector. A challenge in simulating electricity production in an aggregated model is that in reality electricity production depends on a range of complex factors, related to costs, reliance, and the time required to switch on technologies. Modelling these factors requires a high level of detail and thus {{AbbrTemplate|IAM}}s) such as [[TIMER model|TIMER]] concentrate on introducing a set of simplified, meta relationships ([[Hoogwijk, 2004]]; [[Van Vuuren, 2007]]).<br /> <br /> ===Total demand for new capacity===<br /> The electricity capacity required to meet the demand per region is based on a forecast of the maximum electricity demand plus a reserve margin of about 10% (including the capacity credit assigned to different forms of electricity generation). Maximum demand is calculated on the basis of an assumed monthly shape of the load duration curve (LDC) and the gross electricity demand. The latter comprises the net electricity demand from the end-use sectors plus electricity trade and transmission losses ({{AbbrTemplate|LDC}}) accounts for characteristics such as cooling and lighting demand). The demand for new generation capacity is the difference between the required and existing capacity. Power plants are assumed to be replaced at the end of their lifetime, which varies from 30 to 50 years, depending on the technology and is currently fixed in the model.<br /> <br /> ===Decisions to invest in specific options ===<br /> In the following step, a decision is made to invest in different generation technologies. In the model, this is done on the basis of the price of electricity (in USD/kWhe) produced per technology, using a multinomial logit equation that assigns larger market shares to the lower cost options. The specific costs of each option is broken down into a number of categories: investment or capital costs (USD/kWe), fuel costs (USD/GJ), operational and maintenance costs (OM) and other costs (see further). An exception is hydropower capacity, which is exogenously prescribed, because large hydropower plants often have functions other than only electricity production (e.g. water supply and flood control). In the equations, some constraints are added to account for limitations in supply (e.g. restrictions on biomass availability). The investments needed for each option are given in the form of total investment in new generation capacity and the share of each individual technology (determined on the basis of price and preference).<br /> <br /> ===Operational strategy===<br /> Use of power plants is based on operational costs, with low-cost technologies assumed to be used most often. This implies that capital-intensive plants with low operational costs, such as renewable and nuclear energy, operate as many hours as possible. To some degree, this is also true for other plants with low operational costs, such as coal. <br /> The operational decision is presented in the following three steps:<br /> #Renewable sources PV and wind are assigned, followed by hydropower, because these options have the lowest operational costs;<br /> #The peak load capacity (period of high electricity demand) is assigned on the basis of the operational costs of each available plant and the ability of these plants to provide peak load capacity; <br /> #Base load (period of medium to low energy demand) is assigned on the basis of the remaining capacity (after steps 1 and 2), operational costs and the ability of options to provide the base load capacity.<br /> <br /> <br /> ===Fossil-fuel and bio-energy power plants===<br /> A total of 20 types of power plants generating electricity using fossil fuels and bioenergy are included. These power plants represent different combinations of conventional technology, such as gasification and combined cycle (CC) technology; combined heat and power (CHP); and carbon capture and storage ([[CCS]];([[Hendriks et al., 2004b]]). The specific capital costs and thermal efficiencies of these types of plants are determined by exogenous assumptions that describe the technological progress of typical components of these plants:<br /> *For conventional power plants, the coal-fired plant is defined in terms of overall efficiency and investment cost. The characteristics of all other conventional plants (using oil, natural gas or bioenergy) are described in the investment differences for desulphurisation, fuel handling and efficiency.<br /> *For Combined Cycle (CC) power plants, the characteristics of a natural gas fired plant are set as the standard. Other CC plants (fuelled by oil, bioenergy and coal after gasification) are defined by indicating additional capital costs for gasification, efficiency losses due to gasification, and operation and maintenance (O&amp;M) costs for fuel handling. <br /> *Power plants with carbon-capture-and-storage systems (CCS) are assumed to be CC plants, but with fuel-specific lower efficiency and higher investment and O&amp;M costs (related to capture and storage). <br /> *The characteristics of combined-heat-and-power plants (CHP) are similar to those of other plants, but with an assumed small increase in capital costs, in combination with a lower efficiency for electric conversion and an added factor for heat efficiency. <br /> <br /> The cost of one unit electricity generated is equal to the sum of the capital cost, operational and maintenance costs (O&amp;M), fuel cost, and CO2 storage cost.<br /> <br /> ===Solar and wind power===<br /> <br /> The costs of solar and wind power in the model are determined by learning and depletion dynamics. For renewable energy, costs relate to capital, O&amp;M and system integration. The capital costs mostly relate to learning and depletion processes. Learning is represented by in learning curves (Box 4.1.3.1); depletion is by long-term in cost–supply curves. <br /> <br /> The additional system integration costs relate to curtailed electricity (if production exceeds demand and the overcapacity cannot be used within the system), backup capacity; and additional required spinning reserve. The last items are needed to avoid loss of power if the supply of wind or solar power drops suddenly, enabling a power scale up in a relatively short time, in power stations operating below maximum capacity ([[Hoogwijk, 2004]]).<br /> <br /> To determine curtailed electricity, the model compares 10 points on the load-demand curve at the overlap between demand and supply. For both wind and solar power, a typical load supply curve is assumed (see [[Hoogwijk, 2004]]). If supply exceeds demand, the overcapacity in electricity is assumed to be discarded, resulting in higher production costs.<br /> <br /> Because wind and solar power supply is intermittent (variable and thus not reliable), the model assumes that backup capacity needs to be installed. It is assumed that no backup is required for first 5% penetration of the intermittent capacity. However, for higher levels of penetration, the effective capacity (degree to which operators can rely on plants producing at a specific time) of intermittent resources is assumed to decrease. This is referred to as the capacity factor. This decrease leads to the need for backup power by low-cost options, such as gas turbines, the cost of which is allocated to the intermittent source.<br /> <br /> The required spinning reserve of the power system is the capacity that can be used to respond to a rapid increase in demand. This is assumed to be 3.5% of the installed capacity of a conventional power plant. If wind and solar power further penetrate the market, the model assumes an additional, required spinning reserve of 15% of the intermittent capacity (after subtraction of the 3.5% existing capacity). The related costs are allocated to the intermittent source.<br /> <br /> {{FormulaAndTableTemplate|Formula1_ED}}<br /> <br /> ==Nuclear power==<br /> The costs of nuclear power also include capital, O&amp;M and nuclear fuel costs. Similar to the renewable energy options, technology improvement in nuclear power is described via a learning curve (costs decrease with cumulative installed capacity). Fuel costs increase as a function of depletion. Fuel costs are determined on the basis of the estimated extraction costs for uranium and thorium resources, see [[Energy Supply]]. A small trade model for these fission fuels is included..<br /> <br /> ==Hydrogen generation model==<br /> The structure of the hydrogen generation submodule is similar to that for electric power generation ([[Van Ruijven et al., 2007]]) but with following differences:<br /> *There are only eleven supply options for hydrogen production coal, oil, natural gas and bioenergy, with and without carbon capture and storage (8 plants); hydrogen production from electrolysis, direct hydrogen production from solar thermal processes; and small methane reform plants. <br /> *No description of preferences for different power plants is taken into account in the operational strategy. The load factor for each option equals the total production divided by the capacity for each region.<br /> *Intermittence does not play an important role because hydrogen can be stored to some degree. Thus, there are no equations simulating system integration.<br /> *Hydrogen can be traded. A trade model is added, similar to those for fossil fuels described in * [[Energy Supply]].<br /> }}<br /> s such as [[TIMER model|TIMER]] concentrate on introducing a set of simplified, meta relationships ([[Hoogwijk, 2004]]; [[Van Vuuren, 2007]]).<br /> <br /> ===Total demand for new capacity===<br /> The electricity capacity required to meet the demand per region is based on a forecast of the maximum electricity demand plus a reserve margin of about 10% (including the capacity credit assigned to different forms of electricity generation). Maximum demand is calculated on the basis of an assumed monthly shape of the load duration curve (LDC) and the gross electricity demand. The latter comprises the net electricity demand from the end-use sectors plus electricity trade and transmission losses ({{AbbrTemplate|LDC}}) accounts for characteristics such as cooling and lighting demand). The demand for new generation capacity is the difference between the required and existing capacity. Power plants are assumed to be replaced at the end of their lifetime, which varies from 30 to 50 years, depending on the technology and is currently fixed in the model.<br /> <br /> ===Decisions to invest in specific options ===<br /> In the following step, a decision is made to invest in different generation technologies. In the model, this is done on the basis of the price of electricity (in {{AbbrTemplate|USD/kWhe}} produced per technology, using a multinomial logit equation that assigns larger market shares to the lower cost options. The specific costs of each option is broken down into a number of categories: investment or capital costs (USD/kWe), fuel costs ([[HasAcronym::USD/GJ]]), operational and maintenance costs (OM) and other costs (see further). An exception is hydropower capacity, which is exogenously prescribed, because large hydropower plants often have functions other than only electricity production (e.g. water supply and flood control). In the equations, some constraints are added to account for limitations in supply (e.g. restrictions on biomass availability). The investments needed for each option are given in the form of total investment in new generation capacity and the share of each individual technology (determined on the basis of price and preference).<br /> <br /> ===Operational strategy===<br /> Use of power plants is based on operational costs, with low-cost technologies assumed to be used most often. This implies that capital-intensive plants with low operational costs, such as renewable and nuclear energy, operate as many hours as possible. To some degree, this is also true for other plants with low operational costs, such as coal. <br /> The operational decision is presented in the following three steps:<br /> #Renewable sources PV and wind are assigned, followed by hydropower, because these options have the lowest operational costs;<br /> #The peak load capacity (period of high electricity demand) is assigned on the basis of the operational costs of each available plant and the ability of these plants to provide peak load capacity; <br /> #Base load (period of medium to low energy demand) is assigned on the basis of the remaining capacity (after steps 1 and 2), operational costs and the ability of options to provide the base load capacity.<br /> <br /> <br /> ===Fossil-fuel and bio-energy power plants===<br /> A total of 20 types of power plants generating electricity using fossil fuels and bioenergy are included. These power plants represent different combinations of conventional technology, such as gasification and combined cycle (CC) technology; combined heat and power (CHP); and carbon capture and storage (CCS;(Hendriks et al., 2004b). The specific capital costs and thermal efficiencies of these types of plants are determined by exogenous assumptions that describe the technological progress of typical components of these plants:<br /> *For conventional power plants, the coal-fired plant is defined in terms of overall efficiency and investment cost. The characteristics of all other conventional plants (using oil, natural gas or bioenergy) are described in the investment differences for desulphurisation, fuel handling and efficiency.<br /> *For Combined Cycle (CC) power plants, the characteristics of a natural gas fired plant are set as the standard. Other CC plants (fuelled by oil, bioenergy and coal after gasification) are defined by indicating additional capital costs for gasification, efficiency losses due to gasification, and operation and maintenance (O&amp;M) costs for fuel handling. <br /> *Power plants with carbon-capture-and-storage systems (CCS) are assumed to be CC plants, but with fuel-specific lower efficiency and higher investment and O&amp;M costs (related to capture and storage). <br /> *The characteristics of combined-heat-and-power plants (CHP) are similar to those of other plants, but with an assumed small increase in capital costs, in combination with a lower efficiency for electric conversion and an added factor for heat efficiency. <br /> <br /> The cost of one unit electricity generated is equal to the sum of the capital cost, operational and maintenance costs (O&amp;M), fuel cost, and CO2 storage cost.<br /> <br /> ===Solar and wind power===<br /> <br /> The costs of solar and wind power in the model are determined by learning and depletion dynamics. For renewable energy, costs relate to capital, O&amp;M and system integration. The capital costs mostly relate to learning and depletion processes. Learning is represented by in learning curves (Box 4.1.3.1); depletion is by long-term in cost–supply curves. <br /> <br /> The additional system integration costs relate to curtailed electricity (if production exceeds demand and the overcapacity cannot be used within the system), backup capacity; and additional required spinning reserve. The last items are needed to avoid loss of power if the supply of wind or solar power drops suddenly, enabling a power scale up in a relatively short time, in power stations operating below maximum capacity ([[Hoogwijk, 2004]]).<br /> <br /> To determine curtailed electricity, the model compares 10 points on the load-demand curve at the overlap between demand and supply. For both wind and solar power, a typical load supply curve is assumed (see [[Hoogwijk, 2004]]). If supply exceeds demand, the overcapacity in electricity is assumed to be discarded, resulting in higher production costs.<br /> <br /> Because wind and solar power supply is intermittent (variable and thus not reliable), the model assumes that backup capacity needs to be installed. It is assumed that no backup is required for first 5% penetration of the intermittent capacity. However, for higher levels of penetration, the effective capacity (degree to which operators can rely on plants producing at a specific time) of intermittent resources is assumed to decrease. This is referred to as the capacity factor. This decrease leads to the need for backup power by low-cost options, such as gas turbines, the cost of which is allocated to the intermittent source.<br /> <br /> The required spinning reserve of the power system is the capacity that can be used to respond to a rapid increase in demand. This is assumed to be 3.5% of the installed capacity of a conventional power plant. If wind and solar power further penetrate the market, the model assumes an additional, required spinning reserve of 15% of the intermittent capacity (after subtraction of the 3.5% existing capacity). The related costs are allocated to the intermittent source.<br /> <br /> <br /> {{FormulaAndTableTemplate|Formula1_ED}}<br /> <br /> The costs of solar and wind power are the model determined by learning and depletion dynamics. For renewable energy, costs relate to capital, O&amp;M and system integration. The capital costs mostly relate to [[Energy conversion/Description/Technical learning|learning]] and depletion processes (learning is represented by so-called learning curves; depletion is represented by long-term cost–supply curves). <br /> <br /> The additional system integration costs relate to <br /> # Discarded electricity in cases where production exceeds demand and the overcapacity cannot be used within the system;<br /> # Back-up capacity;<br /> # Additional required spinning reserve;<br /> The two last items are needed to avoid loss of power if the supply of wind or solar power suddenly drops, enabling a power scale up in a relatively short time, in power stations operating below maximum capacity ([[Hoogwijk, 2004]]).<br /> *To determine discarded electricity, the model makes a comparison between 10 different points on the load-demand curve, at the overlap between demand and supply. For both wind and solar power, a typical load–supply curve is assumed (see [[Hoogwijk, 2004]]). If supply exceeds demand, the overcapacity in electricity is assumed to be discarded, resulting in higher production costs. <br /> *Because wind and solar power supply is intermittent (i.e. it varies and therefore is not reliable), the model assumes that so-called back-up capacity needs to be installed. For the first 5% penetration of the intermittent capacity, it is assumed that no-back is required. However, for higher levels of penetration, the effective capacity (i.e. degree to which operators can rely on plants producing at a particular moment in time) of intermittent resources is assumed to decrease (referred to as the capacity factor). This decrease leads to the need of back-up power(by low-cost options, such as gas turbines), the costs of which are allocated to the intermittent source.<br /> *The required spinning reserve of the power system (capacity that can be used to respond to a rapid increase in demand) is assumed to be 3.5% of the installed capacity of a conventional power plant. If wind and solar power further penetrate the market, the model assumes an additional, required spinning reserve of 15% of the intermittent capacity (but after first subtracting the 3.5% existing capacity). The related costs are allocated to the intermittent source.<br /> <br /> ==Nuclear power==<br /> For nuclear power, the costs also consists of capital, O&amp;M and nuclear fuel costs. Similar to the renewable energy options, technology improvement nuclear power is described via a learning curve (so costs decrease with cumulative installed capacity). At the same time, fuel costs increase as a function of depletion. Fuel costs are determined on the basis of the estimated extraction costs of uranium and thorium resources, as is described in the component [[Energy supply]]. A small trade model for these fission fuels is included.<br /> <br /> ==Hydrogen generation model==<br /> The structure of the hydrogen model is similar to that of the electric power model ([[Van Ruijven et al., 2007]]). There are, however, some important differences:<br /> *The hydrogen model distinguishes the following 11 supply options: hydrogen production plants on the basis of coal, oil, natural gas and bio-energy, with and <br /> without carbon capture and storage (8 plants), hydrogen production from electrolysis, direct hydrogen production from solar thermal processes, and, finally, small methane reform plants. <br /> *For simplification, no description of preferences for different power plants is accounted for in the operational strategy. In other words, the load factor for each option equals the total production divided by the capacity for each region.<br /> *Intermittence does not play an important role, as hydrogen can be stored to some degree. Therefore, there are no equations simulating system integration.<br /> *Hydrogen can be traded. Therefore, a trade model is added, similar to the trade models for fossil fuels, as is described in the [[Energy supply]] section.<br /> <br /> &lt;references/&gt;<br /> }}</div>

JoeriOostenrijk https://models.pbl.nl/index.php?title=Energy_conversion/Description&diff=21515 2014-05-08T16:10:11Z

<p>JoeriOostenrijk: </p> <hr /> <div>{{ComponentDescriptionTemplate<br /> |Reference=Hoogwijk, 2004; Van Vuuren, 2007; Hendriks et al., 2004b; Van Ruijven et al., 2007;<br /> |Description=[[TIMER model|TIMER]] includes two main energy conversion modules: Electric power generation and hydrogen generation. Below, electric power generation is described in detail. In addition, the key characteristics of the hydrogen generation model, which follows a similar structure, are presented.<br /> <br /> ==Electric power generation==<br /> As shown in the flowchart, two key elements of the electric power generation are the investment strategy and the operational strategy in the sector. A challenge in simulating electricity production in an aggregated model is that in reality electricity production depends on a range of complex factors, related to costs, reliance, and the time required to switch on technologies. Modelling these factors requires a high level of detail and thus ({{AbbrTemplate|IAM}}) such as [[TIMER model|TIMER]] concentrate on introducing a set of simplified, meta relationships ([[Hoogwijk, 2004]]; [[Van Vuuren, 2007]]).<br /> <br /> ===Total demand for new capacity===<br /> The electricity capacity required to meet the demand per region is based on a forecast of the maximum electricity demand plus a reserve margin of about 10% (including the capacity credit assigned to different forms of electricity generation). Maximum demand is calculated on the basis of an assumed monthly shape of the load duration curve (LDC) and the gross electricity demand. The latter comprises the net electricity demand from the end-use sectors plus electricity trade and transmission losses ({{AbbrTemplate|LDC}}) accounts for characteristics such as cooling and lighting demand). The demand for new generation capacity is the difference between the required and existing capacity. Power plants are assumed to be replaced at the end of their lifetime, which varies from 30 to 50 years, depending on the technology and is currently fixed in the model.<br /> <br /> ===Decisions to invest in specific options ===<br /> In the following step, a decision is made to invest in different generation technologies. In the model, this is done on the basis of the price of electricity (in {{AbbrTemplate|USD/kWhe}} produced per technology, using a multinomial logit equation that assigns larger market shares to the lower cost options. The specific costs of each option is broken down into a number of categories: investment or capital costs (USD/kWe), fuel costs ([[HasAcronym::USD/GJ]]), operational and maintenance costs (OM) and other costs (see further). An exception is hydropower capacity, which is exogenously prescribed, because large hydropower plants often have functions other than only electricity production (e.g. water supply and flood control). In the equations, some constraints are added to account for limitations in supply (e.g. restrictions on biomass availability). The investments needed for each option are given in the form of total investment in new generation capacity and the share of each individual technology (determined on the basis of price and preference).<br /> <br /> ===Operational strategy===<br /> Use of power plants is based on operational costs, with low-cost technologies assumed to be used most often. This implies that capital-intensive plants with low operational costs, such as renewable and nuclear energy, operate as many hours as possible. To some degree, this is also true for other plants with low operational costs, such as coal. <br /> The operational decision is presented in the following three steps:<br /> #Renewable sources PV and wind are assigned, followed by hydropower, because these options have the lowest operational costs;<br /> #The peak load capacity (period of high electricity demand) is assigned on the basis of the operational costs of each available plant and the ability of these plants to provide peak load capacity; <br /> #Base load (period of medium to low energy demand) is assigned on the basis of the remaining capacity (after steps 1 and 2), operational costs and the ability of options to provide the base load capacity.<br /> <br /> <br /> ===Fossil-fuel and bio-energy power plants===<br /> A total of 20 types of power plants generating electricity using fossil fuels and bioenergy are included. These power plants represent different combinations of conventional technology, such as gasification and combined cycle (CC) technology; combined heat and power (CHP); and carbon capture and storage (CCS;(Hendriks et al., 2004b). The specific capital costs and thermal efficiencies of these types of plants are determined by exogenous assumptions that describe the technological progress of typical components of these plants:<br /> *For conventional power plants, the coal-fired plant is defined in terms of overall efficiency and investment cost. The characteristics of all other conventional plants (using oil, natural gas or bioenergy) are described in the investment differences for desulphurisation, fuel handling and efficiency.<br /> *For Combined Cycle (CC) power plants, the characteristics of a natural gas fired plant are set as the standard. Other CC plants (fuelled by oil, bioenergy and coal after gasification) are defined by indicating additional capital costs for gasification, efficiency losses due to gasification, and operation and maintenance (O&amp;M) costs for fuel handling. <br /> *Power plants with carbon-capture-and-storage systems (CCS) are assumed to be CC plants, but with fuel-specific lower efficiency and higher investment and O&amp;M costs (related to capture and storage). <br /> *The characteristics of combined-heat-and-power plants (CHP) are similar to those of other plants, but with an assumed small increase in capital costs, in combination with a lower efficiency for electric conversion and an added factor for heat efficiency. <br /> <br /> The cost of one unit electricity generated is equal to the sum of the capital cost, operational and maintenance costs (O&amp;M), fuel cost, and CO2 storage cost.<br /> <br /> ===Solar and wind power===<br /> <br /> The costs of solar and wind power in the model are determined by learning and depletion dynamics. For renewable energy, costs relate to capital, O&amp;M and system integration. The capital costs mostly relate to learning and depletion processes. Learning is represented by in learning curves (Box 4.1.3.1); depletion is by long-term in cost–supply curves. <br /> <br /> The additional system integration costs relate to curtailed electricity (if production exceeds demand and the overcapacity cannot be used within the system), backup capacity; and additional required spinning reserve. The last items are needed to avoid loss of power if the supply of wind or solar power drops suddenly, enabling a power scale up in a relatively short time, in power stations operating below maximum capacity ([[Hoogwijk, 2004]]).<br /> <br /> To determine curtailed electricity, the model compares 10 points on the load-demand curve at the overlap between demand and supply. For both wind and solar power, a typical load supply curve is assumed (see [[Hoogwijk, 2004]]). If supply exceeds demand, the overcapacity in electricity is assumed to be discarded, resulting in higher production costs.<br /> <br /> Because wind and solar power supply is intermittent (variable and thus not reliable), the model assumes that backup capacity needs to be installed. It is assumed that no backup is required for first 5% penetration of the intermittent capacity. However, for higher levels of penetration, the effective capacity (degree to which operators can rely on plants producing at a specific time) of intermittent resources is assumed to decrease. This is referred to as the capacity factor. This decrease leads to the need for backup power by low-cost options, such as gas turbines, the cost of which is allocated to the intermittent source.<br /> <br /> The required spinning reserve of the power system is the capacity that can be used to respond to a rapid increase in demand. This is assumed to be 3.5% of the installed capacity of a conventional power plant. If wind and solar power further penetrate the market, the model assumes an additional, required spinning reserve of 15% of the intermittent capacity (after subtraction of the 3.5% existing capacity). The related costs are allocated to the intermittent source.<br /> <br /> <br /> {{FormulaAndTableTemplate|Formula1_ED}}<br /> <br /> The costs of solar and wind power are the model determined by learning and depletion dynamics. For renewable energy, costs relate to capital, O&amp;M and system integration. The capital costs mostly relate to [[Energy conversion/Description/Technical learning|learning]] and depletion processes (learning is represented by so-called learning curves; depletion is represented by long-term cost–supply curves). <br /> <br /> The additional system integration costs relate to <br /> # Discarded electricity in cases where production exceeds demand and the overcapacity cannot be used within the system;<br /> # Back-up capacity;<br /> # Additional required spinning reserve;<br /> The two last items are needed to avoid loss of power if the supply of wind or solar power suddenly drops, enabling a power scale up in a relatively short time, in power stations operating below maximum capacity ([[Hoogwijk, 2004]]).<br /> *To determine discarded electricity, the model makes a comparison between 10 different points on the load-demand curve, at the overlap between demand and supply. For both wind and solar power, a typical load–supply curve is assumed (see [[Hoogwijk, 2004]]). If supply exceeds demand, the overcapacity in electricity is assumed to be discarded, resulting in higher production costs. <br /> *Because wind and solar power supply is intermittent (i.e. it varies and therefore is not reliable), the model assumes that so-called back-up capacity needs to be installed. For the first 5% penetration of the intermittent capacity, it is assumed that no-back is required. However, for higher levels of penetration, the effective capacity (i.e. degree to which operators can rely on plants producing at a particular moment in time) of intermittent resources is assumed to decrease (referred to as the capacity factor). This decrease leads to the need of back-up power(by low-cost options, such as gas turbines), the costs of which are allocated to the intermittent source.<br /> *The required spinning reserve of the power system (capacity that can be used to respond to a rapid increase in demand) is assumed to be 3.5% of the installed capacity of a conventional power plant. If wind and solar power further penetrate the market, the model assumes an additional, required spinning reserve of 15% of the intermittent capacity (but after first subtracting the 3.5% existing capacity). The related costs are allocated to the intermittent source.<br /> <br /> ==Nuclear power==<br /> For nuclear power, the costs also consists of capital, O&amp;M and nuclear fuel costs. Similar to the renewable energy options, technology improvement nuclear power is described via a learning curve (so costs decrease with cumulative installed capacity). At the same time, fuel costs increase as a function of depletion. Fuel costs are determined on the basis of the estimated extraction costs of uranium and thorium resources, as is described in the component [[Energy supply]]. A small trade model for these fission fuels is included.<br /> <br /> ==Hydrogen generation model==<br /> The structure of the hydrogen model is similar to that of the electric power model ([[Van Ruijven et al., 2007]]). There are, however, some important differences:<br /> *The hydrogen model distinguishes the following 11 supply options: hydrogen production plants on the basis of coal, oil, natural gas and bio-energy, with and <br /> without carbon capture and storage (8 plants), hydrogen production from electrolysis, direct hydrogen production from solar thermal processes, and, finally, small methane reform plants. <br /> *For simplification, no description of preferences for different power plants is accounted for in the operational strategy. In other words, the load factor for each option equals the total production divided by the capacity for each region.<br /> *Intermittence does not play an important role, as hydrogen can be stored to some degree. Therefore, there are no equations simulating system integration.<br /> *Hydrogen can be traded. Therefore, a trade model is added, similar to the trade models for fossil fuels, as is described in the [[Energy supply]] section.<br /> <br /> &lt;references/&gt;<br /> }}<br /> s such as [[TIMER model|TIMER]] concentrate on introducing a set of simplified, meta relationships ([[Hoogwijk, 2004]]; [[Van Vuuren, 2007]]).<br /> <br /> ===Total demand for new capacity===<br /> The electricity capacity required to meet the demand per region is based on a forecast of the maximum electricity demand plus a reserve margin of about 10% (including the capacity credit assigned to different forms of electricity generation). Maximum demand is calculated on the basis of an assumed monthly shape of the load duration curve (LDC) and the gross electricity demand. The latter comprises the net electricity demand from the end-use sectors plus electricity trade and transmission losses ({{AbbrTemplate|LDC}}) accounts for characteristics such as cooling and lighting demand). The demand for new generation capacity is the difference between the required and existing capacity. Power plants are assumed to be replaced at the end of their lifetime, which varies from 30 to 50 years, depending on the technology and is currently fixed in the model.<br /> <br /> ===Decisions to invest in specific options ===<br /> In the following step, a decision is made to invest in different generation technologies. In the model, this is done on the basis of the price of electricity (in {{AbbrTemplate|USD/kWhe}} produced per technology, using a multinomial logit equation that assigns larger market shares to the lower cost options. The specific costs of each option is broken down into a number of categories: investment or capital costs (USD/kWe), fuel costs ([[HasAcronym::USD/GJ]]), operational and maintenance costs (OM) and other costs (see further). An exception is hydropower capacity, which is exogenously prescribed, because large hydropower plants often have functions other than only electricity production (e.g. water supply and flood control). In the equations, some constraints are added to account for limitations in supply (e.g. restrictions on biomass availability). The investments needed for each option are given in the form of total investment in new generation capacity and the share of each individual technology (determined on the basis of price and preference).<br /> <br /> ===Operational strategy===<br /> Use of power plants is based on operational costs, with low-cost technologies assumed to be used most often. This implies that capital-intensive plants with low operational costs, such as renewable and nuclear energy, operate as many hours as possible. To some degree, this is also true for other plants with low operational costs, such as coal. <br /> The operational decision is presented in the following three steps:<br /> #Renewable sources PV and wind are assigned, followed by hydropower, because these options have the lowest operational costs;<br /> #The peak load capacity (period of high electricity demand) is assigned on the basis of the operational costs of each available plant and the ability of these plants to provide peak load capacity; <br /> #Base load (period of medium to low energy demand) is assigned on the basis of the remaining capacity (after steps 1 and 2), operational costs and the ability of options to provide the base load capacity.<br /> <br /> <br /> ===Fossil-fuel and bio-energy power plants===<br /> A total of 20 types of power plants generating electricity using fossil fuels and bioenergy are included. These power plants represent different combinations of conventional technology, such as gasification and combined cycle (CC) technology; combined heat and power (CHP); and carbon capture and storage (CCS;(Hendriks et al., 2004b). The specific capital costs and thermal efficiencies of these types of plants are determined by exogenous assumptions that describe the technological progress of typical components of these plants:<br /> *For conventional power plants, the coal-fired plant is defined in terms of overall efficiency and investment cost. The characteristics of all other conventional plants (using oil, natural gas or bioenergy) are described in the investment differences for desulphurisation, fuel handling and efficiency.<br /> *For Combined Cycle (CC) power plants, the characteristics of a natural gas fired plant are set as the standard. Other CC plants (fuelled by oil, bioenergy and coal after gasification) are defined by indicating additional capital costs for gasification, efficiency losses due to gasification, and operation and maintenance (O&amp;M) costs for fuel handling. <br /> *Power plants with carbon-capture-and-storage systems (CCS) are assumed to be CC plants, but with fuel-specific lower efficiency and higher investment and O&amp;M costs (related to capture and storage). <br /> *The characteristics of combined-heat-and-power plants (CHP) are similar to those of other plants, but with an assumed small increase in capital costs, in combination with a lower efficiency for electric conversion and an added factor for heat efficiency. <br /> <br /> The cost of one unit electricity generated is equal to the sum of the capital cost, operational and maintenance costs (O&amp;M), fuel cost, and CO2 storage cost.<br /> <br /> ===Solar and wind power===<br /> <br /> The costs of solar and wind power in the model are determined by learning and depletion dynamics. For renewable energy, costs relate to capital, O&amp;M and system integration. The capital costs mostly relate to learning and depletion processes. Learning is represented by in learning curves (Box 4.1.3.1); depletion is by long-term in cost–supply curves. <br /> <br /> The additional system integration costs relate to curtailed electricity (if production exceeds demand and the overcapacity cannot be used within the system), backup capacity; and additional required spinning reserve. The last items are needed to avoid loss of power if the supply of wind or solar power drops suddenly, enabling a power scale up in a relatively short time, in power stations operating below maximum capacity ([[Hoogwijk, 2004]]).<br /> <br /> To determine curtailed electricity, the model compares 10 points on the load-demand curve at the overlap between demand and supply. For both wind and solar power, a typical load supply curve is assumed (see [[Hoogwijk, 2004]]). If supply exceeds demand, the overcapacity in electricity is assumed to be discarded, resulting in higher production costs.<br /> <br /> Because wind and solar power supply is intermittent (variable and thus not reliable), the model assumes that backup capacity needs to be installed. It is assumed that no backup is required for first 5% penetration of the intermittent capacity. However, for higher levels of penetration, the effective capacity (degree to which operators can rely on plants producing at a specific time) of intermittent resources is assumed to decrease. This is referred to as the capacity factor. This decrease leads to the need for backup power by low-cost options, such as gas turbines, the cost of which is allocated to the intermittent source.<br /> <br /> The required spinning reserve of the power system is the capacity that can be used to respond to a rapid increase in demand. This is assumed to be 3.5% of the installed capacity of a conventional power plant. If wind and solar power further penetrate the market, the model assumes an additional, required spinning reserve of 15% of the intermittent capacity (after subtraction of the 3.5% existing capacity). The related costs are allocated to the intermittent source.<br /> <br /> <br /> {{FormulaAndTableTemplate|Formula1_ED}}<br /> <br /> The costs of solar and wind power are the model determined by learning and depletion dynamics. For renewable energy, costs relate to capital, O&amp;M and system integration. The capital costs mostly relate to [[Energy conversion/Description/Technical learning|learning]] and depletion processes (learning is represented by so-called learning curves; depletion is represented by long-term cost–supply curves). <br /> <br /> The additional system integration costs relate to <br /> # Discarded electricity in cases where production exceeds demand and the overcapacity cannot be used within the system;<br /> # Back-up capacity;<br /> # Additional required spinning reserve;<br /> The two last items are needed to avoid loss of power if the supply of wind or solar power suddenly drops, enabling a power scale up in a relatively short time, in power stations operating below maximum capacity ([[Hoogwijk, 2004]]).<br /> *To determine discarded electricity, the model makes a comparison between 10 different points on the load-demand curve, at the overlap between demand and supply. For both wind and solar power, a typical load–supply curve is assumed (see [[Hoogwijk, 2004]]). If supply exceeds demand, the overcapacity in electricity is assumed to be discarded, resulting in higher production costs. <br /> *Because wind and solar power supply is intermittent (i.e. it varies and therefore is not reliable), the model assumes that so-called back-up capacity needs to be installed. For the first 5% penetration of the intermittent capacity, it is assumed that no-back is required. However, for higher levels of penetration, the effective capacity (i.e. degree to which operators can rely on plants producing at a particular moment in time) of intermittent resources is assumed to decrease (referred to as the capacity factor). This decrease leads to the need of back-up power(by low-cost options, such as gas turbines), the costs of which are allocated to the intermittent source.<br /> *The required spinning reserve of the power system (capacity that can be used to respond to a rapid increase in demand) is assumed to be 3.5% of the installed capacity of a conventional power plant. If wind and solar power further penetrate the market, the model assumes an additional, required spinning reserve of 15% of the intermittent capacity (but after first subtracting the 3.5% existing capacity). The related costs are allocated to the intermittent source.<br /> <br /> ==Nuclear power==<br /> For nuclear power, the costs also consists of capital, O&amp;M and nuclear fuel costs. Similar to the renewable energy options, technology improvement nuclear power is described via a learning curve (so costs decrease with cumulative installed capacity). At the same time, fuel costs increase as a function of depletion. Fuel costs are determined on the basis of the estimated extraction costs of uranium and thorium resources, as is described in the component [[Energy supply]]. A small trade model for these fission fuels is included.<br /> <br /> ==Hydrogen generation model==<br /> The structure of the hydrogen model is similar to that of the electric power model ([[Van Ruijven et al., 2007]]). There are, however, some important differences:<br /> *The hydrogen model distinguishes the following 11 supply options: hydrogen production plants on the basis of coal, oil, natural gas and bio-energy, with and <br /> without carbon capture and storage (8 plants), hydrogen production from electrolysis, direct hydrogen production from solar thermal processes, and, finally, small methane reform plants. <br /> *For simplification, no description of preferences for different power plants is accounted for in the operational strategy. In other words, the load factor for each option equals the total production divided by the capacity for each region.<br /> *Intermittence does not play an important role, as hydrogen can be stored to some degree. Therefore, there are no equations simulating system integration.<br /> *Hydrogen can be traded. Therefore, a trade model is added, similar to the trade models for fossil fuels, as is described in the [[Energy supply]] section.<br /> <br /> &lt;references/&gt;<br /> }}</div>

JoeriOostenrijk https://models.pbl.nl/index.php?title=Energy_conversion/Description&diff=21514 2014-05-08T16:09:43Z

<p>JoeriOostenrijk: </p> <hr /> <div>{{ComponentDescriptionTemplate<br /> |Reference=Hoogwijk, 2004; Van Vuuren, 2007; Hendriks et al., 2004b; Van Ruijven et al., 2007;<br /> |Description=[[TIMER model|TIMER]] includes two main energy conversion modules: Electric power generation and hydrogen generation. Below, electric power generation is described in detail. In addition, the key characteristics of the hydrogen generation model, which follows a similar structure, are presented.<br /> <br /> ==Electric power generation==<br /> As shown in the flowchart, two key elements of the electric power generation are the investment strategy and the operational strategy in the sector. A challenge in simulating electricity production in an aggregated model is that in reality electricity production depends on a range of complex factors, related to costs, reliance, and the time required to switch on technologies. Modelling these factors requires a high level of detail and thus ({{AbbrTemplate|IAM}}s) such as [[TIMER model|TIMER]] concentrate on introducing a set of simplified, meta relationships ([[Hoogwijk, 2004]]; [[Van Vuuren, 2007]]).<br /> <br /> ===Total demand for new capacity===<br /> The electricity capacity required to meet the demand per region is based on a forecast of the maximum electricity demand plus a reserve margin of about 10% (including the capacity credit assigned to different forms of electricity generation). Maximum demand is calculated on the basis of an assumed monthly shape of the load duration curve (LDC) and the gross electricity demand. The latter comprises the net electricity demand from the end-use sectors plus electricity trade and transmission losses ({{AbbrTemplate|LDC}}) accounts for characteristics such as cooling and lighting demand). The demand for new generation capacity is the difference between the required and existing capacity. Power plants are assumed to be replaced at the end of their lifetime, which varies from 30 to 50 years, depending on the technology and is currently fixed in the model.<br /> <br /> ===Decisions to invest in specific options ===<br /> In the following step, a decision is made to invest in different generation technologies. In the model, this is done on the basis of the price of electricity (in {{AbbrTemplate|USD/kWhe}} produced per technology, using a multinomial logit equation that assigns larger market shares to the lower cost options. The specific costs of each option is broken down into a number of categories: investment or capital costs (USD/kWe), fuel costs ([[HasAcronym::USD/GJ]]), operational and maintenance costs (OM) and other costs (see further). An exception is hydropower capacity, which is exogenously prescribed, because large hydropower plants often have functions other than only electricity production (e.g. water supply and flood control). In the equations, some constraints are added to account for limitations in supply (e.g. restrictions on biomass availability). The investments needed for each option are given in the form of total investment in new generation capacity and the share of each individual technology (determined on the basis of price and preference).<br /> <br /> ===Operational strategy===<br /> Use of power plants is based on operational costs, with low-cost technologies assumed to be used most often. This implies that capital-intensive plants with low operational costs, such as renewable and nuclear energy, operate as many hours as possible. To some degree, this is also true for other plants with low operational costs, such as coal. <br /> The operational decision is presented in the following three steps:<br /> #Renewable sources PV and wind are assigned, followed by hydropower, because these options have the lowest operational costs;<br /> #The peak load capacity (period of high electricity demand) is assigned on the basis of the operational costs of each available plant and the ability of these plants to provide peak load capacity; <br /> #Base load (period of medium to low energy demand) is assigned on the basis of the remaining capacity (after steps 1 and 2), operational costs and the ability of options to provide the base load capacity.<br /> <br /> <br /> ===Fossil-fuel and bio-energy power plants===<br /> A total of 20 types of power plants generating electricity using fossil fuels and bioenergy are included. These power plants represent different combinations of conventional technology, such as gasification and combined cycle (CC) technology; combined heat and power (CHP); and carbon capture and storage (CCS;(Hendriks et al., 2004b). The specific capital costs and thermal efficiencies of these types of plants are determined by exogenous assumptions that describe the technological progress of typical components of these plants:<br /> *For conventional power plants, the coal-fired plant is defined in terms of overall efficiency and investment cost. The characteristics of all other conventional plants (using oil, natural gas or bioenergy) are described in the investment differences for desulphurisation, fuel handling and efficiency.<br /> *For Combined Cycle (CC) power plants, the characteristics of a natural gas fired plant are set as the standard. Other CC plants (fuelled by oil, bioenergy and coal after gasification) are defined by indicating additional capital costs for gasification, efficiency losses due to gasification, and operation and maintenance (O&amp;M) costs for fuel handling. <br /> *Power plants with carbon-capture-and-storage systems (CCS) are assumed to be CC plants, but with fuel-specific lower efficiency and higher investment and O&amp;M costs (related to capture and storage). <br /> *The characteristics of combined-heat-and-power plants (CHP) are similar to those of other plants, but with an assumed small increase in capital costs, in combination with a lower efficiency for electric conversion and an added factor for heat efficiency. <br /> <br /> The cost of one unit electricity generated is equal to the sum of the capital cost, operational and maintenance costs (O&amp;M), fuel cost, and CO2 storage cost.<br /> <br /> ===Solar and wind power===<br /> <br /> The costs of solar and wind power in the model are determined by learning and depletion dynamics. For renewable energy, costs relate to capital, O&amp;M and system integration. The capital costs mostly relate to learning and depletion processes. Learning is represented by in learning curves (Box 4.1.3.1); depletion is by long-term in cost–supply curves. <br /> <br /> The additional system integration costs relate to curtailed electricity (if production exceeds demand and the overcapacity cannot be used within the system), backup capacity; and additional required spinning reserve. The last items are needed to avoid loss of power if the supply of wind or solar power drops suddenly, enabling a power scale up in a relatively short time, in power stations operating below maximum capacity ([[Hoogwijk, 2004]]).<br /> <br /> To determine curtailed electricity, the model compares 10 points on the load-demand curve at the overlap between demand and supply. For both wind and solar power, a typical load supply curve is assumed (see [[Hoogwijk, 2004]]). If supply exceeds demand, the overcapacity in electricity is assumed to be discarded, resulting in higher production costs.<br /> <br /> Because wind and solar power supply is intermittent (variable and thus not reliable), the model assumes that backup capacity needs to be installed. It is assumed that no backup is required for first 5% penetration of the intermittent capacity. However, for higher levels of penetration, the effective capacity (degree to which operators can rely on plants producing at a specific time) of intermittent resources is assumed to decrease. This is referred to as the capacity factor. This decrease leads to the need for backup power by low-cost options, such as gas turbines, the cost of which is allocated to the intermittent source.<br /> <br /> The required spinning reserve of the power system is the capacity that can be used to respond to a rapid increase in demand. This is assumed to be 3.5% of the installed capacity of a conventional power plant. If wind and solar power further penetrate the market, the model assumes an additional, required spinning reserve of 15% of the intermittent capacity (after subtraction of the 3.5% existing capacity). The related costs are allocated to the intermittent source.<br /> <br /> <br /> {{FormulaAndTableTemplate|Formula1_ED}}<br /> <br /> The costs of solar and wind power are the model determined by learning and depletion dynamics. For renewable energy, costs relate to capital, O&amp;M and system integration. The capital costs mostly relate to [[Energy conversion/Description/Technical learning|learning]] and depletion processes (learning is represented by so-called learning curves; depletion is represented by long-term cost–supply curves). <br /> <br /> The additional system integration costs relate to <br /> # Discarded electricity in cases where production exceeds demand and the overcapacity cannot be used within the system;<br /> # Back-up capacity;<br /> # Additional required spinning reserve;<br /> The two last items are needed to avoid loss of power if the supply of wind or solar power suddenly drops, enabling a power scale up in a relatively short time, in power stations operating below maximum capacity ([[Hoogwijk, 2004]]).<br /> *To determine discarded electricity, the model makes a comparison between 10 different points on the load-demand curve, at the overlap between demand and supply. For both wind and solar power, a typical load–supply curve is assumed (see [[Hoogwijk, 2004]]). If supply exceeds demand, the overcapacity in electricity is assumed to be discarded, resulting in higher production costs. <br /> *Because wind and solar power supply is intermittent (i.e. it varies and therefore is not reliable), the model assumes that so-called back-up capacity needs to be installed. For the first 5% penetration of the intermittent capacity, it is assumed that no-back is required. However, for higher levels of penetration, the effective capacity (i.e. degree to which operators can rely on plants producing at a particular moment in time) of intermittent resources is assumed to decrease (referred to as the capacity factor). This decrease leads to the need of back-up power(by low-cost options, such as gas turbines), the costs of which are allocated to the intermittent source.<br /> *The required spinning reserve of the power system (capacity that can be used to respond to a rapid increase in demand) is assumed to be 3.5% of the installed capacity of a conventional power plant. If wind and solar power further penetrate the market, the model assumes an additional, required spinning reserve of 15% of the intermittent capacity (but after first subtracting the 3.5% existing capacity). The related costs are allocated to the intermittent source.<br /> <br /> ==Nuclear power==<br /> For nuclear power, the costs also consists of capital, O&amp;M and nuclear fuel costs. Similar to the renewable energy options, technology improvement nuclear power is described via a learning curve (so costs decrease with cumulative installed capacity). At the same time, fuel costs increase as a function of depletion. Fuel costs are determined on the basis of the estimated extraction costs of uranium and thorium resources, as is described in the component [[Energy supply]]. A small trade model for these fission fuels is included.<br /> <br /> ==Hydrogen generation model==<br /> The structure of the hydrogen model is similar to that of the electric power model ([[Van Ruijven et al., 2007]]). There are, however, some important differences:<br /> *The hydrogen model distinguishes the following 11 supply options: hydrogen production plants on the basis of coal, oil, natural gas and bio-energy, with and <br /> without carbon capture and storage (8 plants), hydrogen production from electrolysis, direct hydrogen production from solar thermal processes, and, finally, small methane reform plants. <br /> *For simplification, no description of preferences for different power plants is accounted for in the operational strategy. In other words, the load factor for each option equals the total production divided by the capacity for each region.<br /> *Intermittence does not play an important role, as hydrogen can be stored to some degree. Therefore, there are no equations simulating system integration.<br /> *Hydrogen can be traded. Therefore, a trade model is added, similar to the trade models for fossil fuels, as is described in the [[Energy supply]] section.<br /> <br /> &lt;references/&gt;<br /> }}<br /> s such as [[TIMER model|TIMER]] concentrate on introducing a set of simplified, meta relationships ([[Hoogwijk, 2004]]; [[Van Vuuren, 2007]]).<br /> <br /> ===Total demand for new capacity===<br /> The electricity capacity required to meet the demand per region is based on a forecast of the maximum electricity demand plus a reserve margin of about 10% (including the capacity credit assigned to different forms of electricity generation). Maximum demand is calculated on the basis of an assumed monthly shape of the load duration curve (LDC) and the gross electricity demand. The latter comprises the net electricity demand from the end-use sectors plus electricity trade and transmission losses ({{AbbrTemplate|LDC}}) accounts for characteristics such as cooling and lighting demand). The demand for new generation capacity is the difference between the required and existing capacity. Power plants are assumed to be replaced at the end of their lifetime, which varies from 30 to 50 years, depending on the technology and is currently fixed in the model.<br /> <br /> ===Decisions to invest in specific options ===<br /> In the following step, a decision is made to invest in different generation technologies. In the model, this is done on the basis of the price of electricity (in {{AbbrTemplate|USD/kWhe}} produced per technology, using a multinomial logit equation that assigns larger market shares to the lower cost options. The specific costs of each option is broken down into a number of categories: investment or capital costs (USD/kWe), fuel costs ([[HasAcronym::USD/GJ]]), operational and maintenance costs (OM) and other costs (see further). An exception is hydropower capacity, which is exogenously prescribed, because large hydropower plants often have functions other than only electricity production (e.g. water supply and flood control). In the equations, some constraints are added to account for limitations in supply (e.g. restrictions on biomass availability). The investments needed for each option are given in the form of total investment in new generation capacity and the share of each individual technology (determined on the basis of price and preference).<br /> <br /> ===Operational strategy===<br /> Use of power plants is based on operational costs, with low-cost technologies assumed to be used most often. This implies that capital-intensive plants with low operational costs, such as renewable and nuclear energy, operate as many hours as possible. To some degree, this is also true for other plants with low operational costs, such as coal. <br /> The operational decision is presented in the following three steps:<br /> #Renewable sources PV and wind are assigned, followed by hydropower, because these options have the lowest operational costs;<br /> #The peak load capacity (period of high electricity demand) is assigned on the basis of the operational costs of each available plant and the ability of these plants to provide peak load capacity; <br /> #Base load (period of medium to low energy demand) is assigned on the basis of the remaining capacity (after steps 1 and 2), operational costs and the ability of options to provide the base load capacity.<br /> <br /> <br /> ===Fossil-fuel and bio-energy power plants===<br /> A total of 20 types of power plants generating electricity using fossil fuels and bioenergy are included. These power plants represent different combinations of conventional technology, such as gasification and combined cycle (CC) technology; combined heat and power (CHP); and carbon capture and storage (CCS;(Hendriks et al., 2004b). The specific capital costs and thermal efficiencies of these types of plants are determined by exogenous assumptions that describe the technological progress of typical components of these plants:<br /> *For conventional power plants, the coal-fired plant is defined in terms of overall efficiency and investment cost. The characteristics of all other conventional plants (using oil, natural gas or bioenergy) are described in the investment differences for desulphurisation, fuel handling and efficiency.<br /> *For Combined Cycle (CC) power plants, the characteristics of a natural gas fired plant are set as the standard. Other CC plants (fuelled by oil, bioenergy and coal after gasification) are defined by indicating additional capital costs for gasification, efficiency losses due to gasification, and operation and maintenance (O&amp;M) costs for fuel handling. <br /> *Power plants with carbon-capture-and-storage systems (CCS) are assumed to be CC plants, but with fuel-specific lower efficiency and higher investment and O&amp;M costs (related to capture and storage). <br /> *The characteristics of combined-heat-and-power plants (CHP) are similar to those of other plants, but with an assumed small increase in capital costs, in combination with a lower efficiency for electric conversion and an added factor for heat efficiency. <br /> <br /> The cost of one unit electricity generated is equal to the sum of the capital cost, operational and maintenance costs (O&amp;M), fuel cost, and CO2 storage cost.<br /> <br /> ===Solar and wind power===<br /> <br /> The costs of solar and wind power in the model are determined by learning and depletion dynamics. For renewable energy, costs relate to capital, O&amp;M and system integration. The capital costs mostly relate to learning and depletion processes. Learning is represented by in learning curves (Box 4.1.3.1); depletion is by long-term in cost–supply curves. <br /> <br /> The additional system integration costs relate to curtailed electricity (if production exceeds demand and the overcapacity cannot be used within the system), backup capacity; and additional required spinning reserve. The last items are needed to avoid loss of power if the supply of wind or solar power drops suddenly, enabling a power scale up in a relatively short time, in power stations operating below maximum capacity ([[Hoogwijk, 2004]]).<br /> <br /> To determine curtailed electricity, the model compares 10 points on the load-demand curve at the overlap between demand and supply. For both wind and solar power, a typical load supply curve is assumed (see [[Hoogwijk, 2004]]). If supply exceeds demand, the overcapacity in electricity is assumed to be discarded, resulting in higher production costs.<br /> <br /> Because wind and solar power supply is intermittent (variable and thus not reliable), the model assumes that backup capacity needs to be installed. It is assumed that no backup is required for first 5% penetration of the intermittent capacity. However, for higher levels of penetration, the effective capacity (degree to which operators can rely on plants producing at a specific time) of intermittent resources is assumed to decrease. This is referred to as the capacity factor. This decrease leads to the need for backup power by low-cost options, such as gas turbines, the cost of which is allocated to the intermittent source.<br /> <br /> The required spinning reserve of the power system is the capacity that can be used to respond to a rapid increase in demand. This is assumed to be 3.5% of the installed capacity of a conventional power plant. If wind and solar power further penetrate the market, the model assumes an additional, required spinning reserve of 15% of the intermittent capacity (after subtraction of the 3.5% existing capacity). The related costs are allocated to the intermittent source.<br /> <br /> <br /> {{FormulaAndTableTemplate|Formula1_ED}}<br /> <br /> The costs of solar and wind power are the model determined by learning and depletion dynamics. For renewable energy, costs relate to capital, O&amp;M and system integration. The capital costs mostly relate to [[Energy conversion/Description/Technical learning|learning]] and depletion processes (learning is represented by so-called learning curves; depletion is represented by long-term cost–supply curves). <br /> <br /> The additional system integration costs relate to <br /> # Discarded electricity in cases where production exceeds demand and the overcapacity cannot be used within the system;<br /> # Back-up capacity;<br /> # Additional required spinning reserve;<br /> The two last items are needed to avoid loss of power if the supply of wind or solar power suddenly drops, enabling a power scale up in a relatively short time, in power stations operating below maximum capacity ([[Hoogwijk, 2004]]).<br /> *To determine discarded electricity, the model makes a comparison between 10 different points on the load-demand curve, at the overlap between demand and supply. For both wind and solar power, a typical load–supply curve is assumed (see [[Hoogwijk, 2004]]). If supply exceeds demand, the overcapacity in electricity is assumed to be discarded, resulting in higher production costs. <br /> *Because wind and solar power supply is intermittent (i.e. it varies and therefore is not reliable), the model assumes that so-called back-up capacity needs to be installed. For the first 5% penetration of the intermittent capacity, it is assumed that no-back is required. However, for higher levels of penetration, the effective capacity (i.e. degree to which operators can rely on plants producing at a particular moment in time) of intermittent resources is assumed to decrease (referred to as the capacity factor). This decrease leads to the need of back-up power(by low-cost options, such as gas turbines), the costs of which are allocated to the intermittent source.<br /> *The required spinning reserve of the power system (capacity that can be used to respond to a rapid increase in demand) is assumed to be 3.5% of the installed capacity of a conventional power plant. If wind and solar power further penetrate the market, the model assumes an additional, required spinning reserve of 15% of the intermittent capacity (but after first subtracting the 3.5% existing capacity). The related costs are allocated to the intermittent source.<br /> <br /> ==Nuclear power==<br /> For nuclear power, the costs also consists of capital, O&amp;M and nuclear fuel costs. Similar to the renewable energy options, technology improvement nuclear power is described via a learning curve (so costs decrease with cumulative installed capacity). At the same time, fuel costs increase as a function of depletion. Fuel costs are determined on the basis of the estimated extraction costs of uranium and thorium resources, as is described in the component [[Energy supply]]. A small trade model for these fission fuels is included.<br /> <br /> ==Hydrogen generation model==<br /> The structure of the hydrogen model is similar to that of the electric power model ([[Van Ruijven et al., 2007]]). There are, however, some important differences:<br /> *The hydrogen model distinguishes the following 11 supply options: hydrogen production plants on the basis of coal, oil, natural gas and bio-energy, with and <br /> without carbon capture and storage (8 plants), hydrogen production from electrolysis, direct hydrogen production from solar thermal processes, and, finally, small methane reform plants. <br /> *For simplification, no description of preferences for different power plants is accounted for in the operational strategy. In other words, the load factor for each option equals the total production divided by the capacity for each region.<br /> *Intermittence does not play an important role, as hydrogen can be stored to some degree. Therefore, there are no equations simulating system integration.<br /> *Hydrogen can be traded. Therefore, a trade model is added, similar to the trade models for fossil fuels, as is described in the [[Energy supply]] section.<br /> <br /> &lt;references/&gt;<br /> }}</div>

JoeriOostenrijk https://models.pbl.nl/index.php?title=Energy_conversion/Description&diff=21512 2014-05-08T15:53:49Z

<p>JoeriOostenrijk: </p> <hr /> <div>{{ComponentDescriptionTemplate<br /> |Reference=Hoogwijk, 2004; Van Vuuren, 2007; Hendriks et al., 2004b; Van Ruijven et al., 2007;<br /> |Description=[[TIMER model|TIMER]] includes two main energy conversion modules: Electric power generation and hydrogen generation. Below, electric power generation is described in detail. In addition, the key characteristics of the hydrogen generation model, which follows a similar structure, are presented.<br /> <br /> ==Electric power generation==<br /> As shown in the flowchart, two key elements of the electric power generation are the investment strategy and the operational strategy in the sector. A challenge in simulating electricity production in an aggregated model is that in reality electricity production depends on a range of complex factors, related to costs, reliance, and the time required to switch on technologies. Modelling these factors requires a high level of detail and thus {{AbbrTemplate|IAM}}s such as [[TIMER model|TIMER]] concentrate on introducing a set of simplified, meta relationships ([[Hoogwijk, 2004]]; [[Van Vuuren, 2007]]).<br /> <br /> ===Total demand for new capacity===<br /> The electricity capacity required to meet the demand per region is based on a forecast of the maximum electricity demand plus a reserve margin of about 10% (including the capacity credit assigned to different forms of electricity generation). Maximum demand is calculated on the basis of an assumed monthly shape of the load duration curve (LDC) and the gross electricity demand. The latter comprises the net electricity demand from the end-use sectors plus electricity trade and transmission losses ({{AbbrTemplate|LDC}}) accounts for characteristics such as cooling and lighting demand). The demand for new generation capacity is the difference between the required and existing capacity. Power plants are assumed to be replaced at the end of their lifetime, which varies from 30 to 50 years, depending on the technology and is currently fixed in the model.<br /> <br /> ===Decisions to invest in specific options ===<br /> In the following step, a decision is made to invest in different generation technologies. In the model, this is done on the basis of the price of electricity (in {{AbbrTemplate|USD/kWhe}} produced per technology, using a multinomial logit equation that assigns larger market shares to the lower cost options. The specific costs of each option is broken down into a number of categories: investment or capital costs (USD/kWe), fuel costs ([[HasAcronym::USD/GJ]]), operational and maintenance costs (OM) and other costs (see further). An exception is hydropower capacity, which is exogenously prescribed, because large hydropower plants often have functions other than only electricity production (e.g. water supply and flood control). In the equations, some constraints are added to account for limitations in supply (e.g. restrictions on biomass availability). The investments needed for each option are given in the form of total investment in new generation capacity and the share of each individual technology (determined on the basis of price and preference).<br /> <br /> ===Operational strategy===<br /> Use of power plants is based on operational costs, with low-cost technologies assumed to be used most often. This implies that capital-intensive plants with low operational costs, such as renewable and nuclear energy, operate as many hours as possible. To some degree, this is also true for other plants with low operational costs, such as coal. <br /> The operational decision is presented in the following three steps:<br /> #Renewable sources PV and wind are assigned, followed by hydropower, because these options have the lowest operational costs;<br /> #The peak load capacity (period of high electricity demand) is assigned on the basis of the operational costs of each available plant and the ability of these plants to provide peak load capacity; <br /> #Base load (period of medium to low energy demand) is assigned on the basis of the remaining capacity (after steps 1 and 2), operational costs and the ability of options to provide the base load capacity.<br /> <br /> <br /> ===Fossil-fuel and bio-energy power plants===<br /> A total of 20 types of power plants generating electricity using fossil fuels and bioenergy are included. These power plants represent different combinations of conventional technology, such as gasification and combined cycle (CC) technology; combined heat and power (CHP); and carbon capture and storage (CCS;(Hendriks et al., 2004b). The specific capital costs and thermal efficiencies of these types of plants are determined by exogenous assumptions that describe the technological progress of typical components of these plants:<br /> *For conventional power plants, the coal-fired plant is defined in terms of overall efficiency and investment cost. The characteristics of all other conventional plants (using oil, natural gas or bioenergy) are described in the investment differences for desulphurisation, fuel handling and efficiency.<br /> *For Combined Cycle (CC) power plants, the characteristics of a natural gas fired plant are set as the standard. Other CC plants (fuelled by oil, bioenergy and coal after gasification) are defined by indicating additional capital costs for gasification, efficiency losses due to gasification, and operation and maintenance (O&amp;M) costs for fuel handling. <br /> *Power plants with carbon-capture-and-storage systems (CCS) are assumed to be CC plants, but with fuel-specific lower efficiency and higher investment and O&amp;M costs (related to capture and storage). <br /> *The characteristics of combined-heat-and-power plants (CHP) are similar to those of other plants, but with an assumed small increase in capital costs, in combination with a lower efficiency for electric conversion and an added factor for heat efficiency. <br /> <br /> The cost of one unit electricity generated is equal to the sum of the capital cost, operational and maintenance costs (O&amp;M), fuel cost, and CO2 storage cost.<br /> <br /> ===Solar and wind power===<br /> <br /> The costs of solar and wind power in the model are determined by learning and depletion dynamics. For renewable energy, costs relate to capital, O&amp;M and system integration. The capital costs mostly relate to learning and depletion processes. Learning is represented by in learning curves (Box 4.1.3.1); depletion is by long-term in cost–supply curves. <br /> <br /> The additional system integration costs relate to curtailed electricity (if production exceeds demand and the overcapacity cannot be used within the system), backup capacity; and additional required spinning reserve. The last items are needed to avoid loss of power if the supply of wind or solar power drops suddenly, enabling a power scale up in a relatively short time, in power stations operating below maximum capacity ([[Hoogwijk, 2004]]).<br /> <br /> To determine curtailed electricity, the model compares 10 points on the load-demand curve at the overlap between demand and supply. For both wind and solar power, a typical load supply curve is assumed (see [[Hoogwijk, 2004]]). If supply exceeds demand, the overcapacity in electricity is assumed to be discarded, resulting in higher production costs.<br /> <br /> Because wind and solar power supply is intermittent (variable and thus not reliable), the model assumes that backup capacity needs to be installed. It is assumed that no backup is required for first 5% penetration of the intermittent capacity. However, for higher levels of penetration, the effective capacity (degree to which operators can rely on plants producing at a specific time) of intermittent resources is assumed to decrease. This is referred to as the capacity factor. This decrease leads to the need for backup power by low-cost options, such as gas turbines, the cost of which is allocated to the intermittent source.<br /> <br /> The required spinning reserve of the power system is the capacity that can be used to respond to a rapid increase in demand. This is assumed to be 3.5% of the installed capacity of a conventional power plant. If wind and solar power further penetrate the market, the model assumes an additional, required spinning reserve of 15% of the intermittent capacity (after subtraction of the 3.5% existing capacity). The related costs are allocated to the intermittent source.<br /> <br /> <br /> {{FormulaAndTableTemplate|Formula1_ED}}<br /> <br /> The costs of solar and wind power are the model determined by learning and depletion dynamics. For renewable energy, costs relate to capital, O&amp;M and system integration. The capital costs mostly relate to [[Energy conversion/Description/Technical learning|learning]] and depletion processes (learning is represented by so-called learning curves; depletion is represented by long-term cost–supply curves). <br /> <br /> The additional system integration costs relate to <br /> # Discarded electricity in cases where production exceeds demand and the overcapacity cannot be used within the system;<br /> # Back-up capacity;<br /> # Additional required spinning reserve;<br /> The two last items are needed to avoid loss of power if the supply of wind or solar power suddenly drops, enabling a power scale up in a relatively short time, in power stations operating below maximum capacity ([[Hoogwijk, 2004]]).<br /> *To determine discarded electricity, the model makes a comparison between 10 different points on the load-demand curve, at the overlap between demand and supply. For both wind and solar power, a typical load–supply curve is assumed (see [[Hoogwijk, 2004]]). If supply exceeds demand, the overcapacity in electricity is assumed to be discarded, resulting in higher production costs. <br /> *Because wind and solar power supply is intermittent (i.e. it varies and therefore is not reliable), the model assumes that so-called back-up capacity needs to be installed. For the first 5% penetration of the intermittent capacity, it is assumed that no-back is required. However, for higher levels of penetration, the effective capacity (i.e. degree to which operators can rely on plants producing at a particular moment in time) of intermittent resources is assumed to decrease (referred to as the capacity factor). This decrease leads to the need of back-up power(by low-cost options, such as gas turbines), the costs of which are allocated to the intermittent source.<br /> *The required spinning reserve of the power system (capacity that can be used to respond to a rapid increase in demand) is assumed to be 3.5% of the installed capacity of a conventional power plant. If wind and solar power further penetrate the market, the model assumes an additional, required spinning reserve of 15% of the intermittent capacity (but after first subtracting the 3.5% existing capacity). The related costs are allocated to the intermittent source.<br /> <br /> ==Nuclear power==<br /> For nuclear power, the costs also consists of capital, O&amp;M and nuclear fuel costs. Similar to the renewable energy options, technology improvement nuclear power is described via a learning curve (so costs decrease with cumulative installed capacity). At the same time, fuel costs increase as a function of depletion. Fuel costs are determined on the basis of the estimated extraction costs of uranium and thorium resources, as is described in the component [[Energy supply]]. A small trade model for these fission fuels is included.<br /> <br /> ==Hydrogen generation model==<br /> The structure of the hydrogen model is similar to that of the electric power model ([[Van Ruijven et al., 2007]]). There are, however, some important differences:<br /> *The hydrogen model distinguishes the following 11 supply options: hydrogen production plants on the basis of coal, oil, natural gas and bio-energy, with and <br /> without carbon capture and storage (8 plants), hydrogen production from electrolysis, direct hydrogen production from solar thermal processes, and, finally, small methane reform plants. <br /> *For simplification, no description of preferences for different power plants is accounted for in the operational strategy. In other words, the load factor for each option equals the total production divided by the capacity for each region.<br /> *Intermittence does not play an important role, as hydrogen can be stored to some degree. Therefore, there are no equations simulating system integration.<br /> *Hydrogen can be traded. Therefore, a trade model is added, similar to the trade models for fossil fuels, as is described in the [[Energy supply]] section.<br /> <br /> &lt;references/&gt;<br /> }}<br /> s such as [[TIMER model|TIMER]] concentrate on introducing a set of simplified, meta relationships ([[Hoogwijk, 2004]]; [[Van Vuuren, 2007]]).<br /> <br /> ===Total demand for new capacity===<br /> The electricity capacity required to meet the demand per region is based on a forecast of the maximum electricity demand plus a reserve margin of about 10% (including the capacity credit assigned to different forms of electricity generation). Maximum demand is calculated on the basis of an assumed monthly shape of the load duration curve (LDC) and the gross electricity demand. The latter comprises the net electricity demand from the end-use sectors plus electricity trade and transmission losses ({{AbbrTemplate|LDC}}) accounts for characteristics such as cooling and lighting demand). The demand for new generation capacity is the difference between the required and existing capacity. Power plants are assumed to be replaced at the end of their lifetime, which varies from 30 to 50 years, depending on the technology and is currently fixed in the model.<br /> <br /> ===Decisions to invest in specific options ===<br /> In the following step, a decision is made to invest in different generation technologies. In the model, this is done on the basis of the price of electricity (in {{AbbrTemplate|USD/kWhe}} produced per technology, using a multinomial logit equation that assigns larger market shares to the lower cost options. The specific costs of each option is broken down into a number of categories: investment or capital costs (USD/kWe), fuel costs ([[HasAcronym::USD/GJ]]), operational and maintenance costs (OM) and other costs (see further). An exception is hydropower capacity, which is exogenously prescribed, because large hydropower plants often have functions other than only electricity production (e.g. water supply and flood control). In the equations, some constraints are added to account for limitations in supply (e.g. restrictions on biomass availability). The investments needed for each option are given in the form of total investment in new generation capacity and the share of each individual technology (determined on the basis of price and preference).<br /> <br /> ===Operational strategy===<br /> Use of power plants is based on operational costs, with low-cost technologies assumed to be used most often. This implies that capital-intensive plants with low operational costs, such as renewable and nuclear energy, operate as many hours as possible. To some degree, this is also true for other plants with low operational costs, such as coal. <br /> The operational decision is presented in the following three steps:<br /> #Renewable sources PV and wind are assigned, followed by hydropower, because these options have the lowest operational costs;<br /> #The peak load capacity (period of high electricity demand) is assigned on the basis of the operational costs of each available plant and the ability of these plants to provide peak load capacity; <br /> #Base load (period of medium to low energy demand) is assigned on the basis of the remaining capacity (after steps 1 and 2), operational costs and the ability of options to provide the base load capacity.<br /> <br /> <br /> ===Fossil-fuel and bio-energy power plants===<br /> A total of 20 types of power plants generating electricity using fossil fuels and bioenergy are included. These power plants represent different combinations of conventional technology, such as gasification and combined cycle (CC) technology; combined heat and power (CHP); and carbon capture and storage (CCS;(Hendriks et al., 2004b). The specific capital costs and thermal efficiencies of these types of plants are determined by exogenous assumptions that describe the technological progress of typical components of these plants:<br /> *For conventional power plants, the coal-fired plant is defined in terms of overall efficiency and investment cost. The characteristics of all other conventional plants (using oil, natural gas or bioenergy) are described in the investment differences for desulphurisation, fuel handling and efficiency.<br /> *For Combined Cycle (CC) power plants, the characteristics of a natural gas fired plant are set as the standard. Other CC plants (fuelled by oil, bioenergy and coal after gasification) are defined by indicating additional capital costs for gasification, efficiency losses due to gasification, and operation and maintenance (O&amp;M) costs for fuel handling. <br /> *Power plants with carbon-capture-and-storage systems (CCS) are assumed to be CC plants, but with fuel-specific lower efficiency and higher investment and O&amp;M costs (related to capture and storage). <br /> *The characteristics of combined-heat-and-power plants (CHP) are similar to those of other plants, but with an assumed small increase in capital costs, in combination with a lower efficiency for electric conversion and an added factor for heat efficiency. <br /> <br /> The cost of one unit electricity generated is equal to the sum of the capital cost, operational and maintenance costs (O&amp;M), fuel cost, and CO2 storage cost.<br /> <br /> ===Solar and wind power===<br /> <br /> The costs of solar and wind power in the model are determined by learning and depletion dynamics. For renewable energy, costs relate to capital, O&amp;M and system integration. The capital costs mostly relate to learning and depletion processes. Learning is represented by in learning curves (Box 4.1.3.1); depletion is by long-term in cost–supply curves. <br /> <br /> The additional system integration costs relate to curtailed electricity (if production exceeds demand and the overcapacity cannot be used within the system), backup capacity; and additional required spinning reserve. The last items are needed to avoid loss of power if the supply of wind or solar power drops suddenly, enabling a power scale up in a relatively short time, in power stations operating below maximum capacity ([[Hoogwijk, 2004]]).<br /> <br /> To determine curtailed electricity, the model compares 10 points on the load-demand curve at the overlap between demand and supply. For both wind and solar power, a typical load supply curve is assumed (see [[Hoogwijk, 2004]]). If supply exceeds demand, the overcapacity in electricity is assumed to be discarded, resulting in higher production costs.<br /> <br /> Because wind and solar power supply is intermittent (variable and thus not reliable), the model assumes that backup capacity needs to be installed. It is assumed that no backup is required for first 5% penetration of the intermittent capacity. However, for higher levels of penetration, the effective capacity (degree to which operators can rely on plants producing at a specific time) of intermittent resources is assumed to decrease. This is referred to as the capacity factor. This decrease leads to the need for backup power by low-cost options, such as gas turbines, the cost of which is allocated to the intermittent source.<br /> <br /> The required spinning reserve of the power system is the capacity that can be used to respond to a rapid increase in demand. This is assumed to be 3.5% of the installed capacity of a conventional power plant. If wind and solar power further penetrate the market, the model assumes an additional, required spinning reserve of 15% of the intermittent capacity (after subtraction of the 3.5% existing capacity). The related costs are allocated to the intermittent source.<br /> <br /> <br /> {{FormulaAndTableTemplate|Formula1_ED}}<br /> <br /> The costs of solar and wind power are the model determined by learning and depletion dynamics. For renewable energy, costs relate to capital, O&amp;M and system integration. The capital costs mostly relate to [[Energy conversion/Description/Technical learning|learning]] and depletion processes (learning is represented by so-called learning curves; depletion is represented by long-term cost–supply curves). <br /> <br /> The additional system integration costs relate to <br /> # Discarded electricity in cases where production exceeds demand and the overcapacity cannot be used within the system;<br /> # Back-up capacity;<br /> # Additional required spinning reserve;<br /> The two last items are needed to avoid loss of power if the supply of wind or solar power suddenly drops, enabling a power scale up in a relatively short time, in power stations operating below maximum capacity ([[Hoogwijk, 2004]]).<br /> *To determine discarded electricity, the model makes a comparison between 10 different points on the load-demand curve, at the overlap between demand and supply. For both wind and solar power, a typical load–supply curve is assumed (see [[Hoogwijk, 2004]]). If supply exceeds demand, the overcapacity in electricity is assumed to be discarded, resulting in higher production costs. <br /> *Because wind and solar power supply is intermittent (i.e. it varies and therefore is not reliable), the model assumes that so-called back-up capacity needs to be installed. For the first 5% penetration of the intermittent capacity, it is assumed that no-back is required. However, for higher levels of penetration, the effective capacity (i.e. degree to which operators can rely on plants producing at a particular moment in time) of intermittent resources is assumed to decrease (referred to as the capacity factor). This decrease leads to the need of back-up power(by low-cost options, such as gas turbines), the costs of which are allocated to the intermittent source.<br /> *The required spinning reserve of the power system (capacity that can be used to respond to a rapid increase in demand) is assumed to be 3.5% of the installed capacity of a conventional power plant. If wind and solar power further penetrate the market, the model assumes an additional, required spinning reserve of 15% of the intermittent capacity (but after first subtracting the 3.5% existing capacity). The related costs are allocated to the intermittent source.<br /> <br /> ==Nuclear power==<br /> For nuclear power, the costs also consists of capital, O&amp;M and nuclear fuel costs. Similar to the renewable energy options, technology improvement nuclear power is described via a learning curve (so costs decrease with cumulative installed capacity). At the same time, fuel costs increase as a function of depletion. Fuel costs are determined on the basis of the estimated extraction costs of uranium and thorium resources, as is described in the component [[Energy supply]]. A small trade model for these fission fuels is included.<br /> <br /> ==Hydrogen generation model==<br /> The structure of the hydrogen model is similar to that of the electric power model ([[Van Ruijven et al., 2007]]). There are, however, some important differences:<br /> *The hydrogen model distinguishes the following 11 supply options: hydrogen production plants on the basis of coal, oil, natural gas and bio-energy, with and <br /> without carbon capture and storage (8 plants), hydrogen production from electrolysis, direct hydrogen production from solar thermal processes, and, finally, small methane reform plants. <br /> *For simplification, no description of preferences for different power plants is accounted for in the operational strategy. In other words, the load factor for each option equals the total production divided by the capacity for each region.<br /> *Intermittence does not play an important role, as hydrogen can be stored to some degree. Therefore, there are no equations simulating system integration.<br /> *Hydrogen can be traded. Therefore, a trade model is added, similar to the trade models for fossil fuels, as is described in the [[Energy supply]] section.<br /> <br /> &lt;references/&gt;<br /> }}</div>

JoeriOostenrijk https://models.pbl.nl/index.php?title=Energy_conversion/Description&diff=21511 2014-05-08T15:52:59Z

<p>JoeriOostenrijk: </p> <hr /> <div>{{ComponentDescriptionTemplate<br /> |Reference=Hoogwijk, 2004; Van Vuuren, 2007; Hendriks et al., 2004b; Van Ruijven et al., 2007;<br /> |Description=[[TIMER model|TIMER]] includes two main energy conversion modules: Electric power generation and hydrogen generation. Below, electric power generation is described in detail. In addition, the key characteristics of the hydrogen generation model, which follows a similar structure, are presented.<br /> <br /> ==Electric power generation==<br /> As shown in the flowchart, two key elements of the electric power generation are the investment strategy and the operational strategy in the sector. A challenge in simulating electricity production in an aggregated model is that in reality electricity production depends on a range of complex factors, related to costs, reliance, and the time required to switch on technologies. Modelling these factors requires a high level of detail and thus {{AbbrTemplate|IAM}} such as [[TIMER model|TIMER]] concentrate on introducing a set of simplified, meta relationships ([[Hoogwijk, 2004]]; [[Van Vuuren, 2007]]).<br /> <br /> ===Total demand for new capacity===<br /> The electricity capacity required to meet the demand per region is based on a forecast of the maximum electricity demand plus a reserve margin of about 10% (including the capacity credit assigned to different forms of electricity generation). Maximum demand is calculated on the basis of an assumed monthly shape of the load duration curve (LDC) and the gross electricity demand. The latter comprises the net electricity demand from the end-use sectors plus electricity trade and transmission losses ({{AbbrTemplate|LDC}}) accounts for characteristics such as cooling and lighting demand). The demand for new generation capacity is the difference between the required and existing capacity. Power plants are assumed to be replaced at the end of their lifetime, which varies from 30 to 50 years, depending on the technology and is currently fixed in the model.<br /> <br /> ===Decisions to invest in specific options ===<br /> In the following step, a decision is made to invest in different generation technologies. In the model, this is done on the basis of the price of electricity (in {{AbbrTemplate|USD/kWhe}} produced per technology, using a multinomial logit equation that assigns larger market shares to the lower cost options. The specific costs of each option is broken down into a number of categories: investment or capital costs (USD/kWe), fuel costs ([[HasAcronym::USD/GJ]]), operational and maintenance costs (OM) and other costs (see further). An exception is hydropower capacity, which is exogenously prescribed, because large hydropower plants often have functions other than only electricity production (e.g. water supply and flood control). In the equations, some constraints are added to account for limitations in supply (e.g. restrictions on biomass availability). The investments needed for each option are given in the form of total investment in new generation capacity and the share of each individual technology (determined on the basis of price and preference).<br /> <br /> ===Operational strategy===<br /> Use of power plants is based on operational costs, with low-cost technologies assumed to be used most often. This implies that capital-intensive plants with low operational costs, such as renewable and nuclear energy, operate as many hours as possible. To some degree, this is also true for other plants with low operational costs, such as coal. <br /> The operational decision is presented in the following three steps:<br /> #Renewable sources PV and wind are assigned, followed by hydropower, because these options have the lowest operational costs;<br /> #The peak load capacity (period of high electricity demand) is assigned on the basis of the operational costs of each available plant and the ability of these plants to provide peak load capacity; <br /> #Base load (period of medium to low energy demand) is assigned on the basis of the remaining capacity (after steps 1 and 2), operational costs and the ability of options to provide the base load capacity.<br /> <br /> <br /> ===Fossil-fuel and bio-energy power plants===<br /> A total of 20 types of power plants generating electricity using fossil fuels and bioenergy are included. These power plants represent different combinations of conventional technology, such as gasification and combined cycle (CC) technology; combined heat and power (CHP); and carbon capture and storage (CCS;(Hendriks et al., 2004b). The specific capital costs and thermal efficiencies of these types of plants are determined by exogenous assumptions that describe the technological progress of typical components of these plants:<br /> *For conventional power plants, the coal-fired plant is defined in terms of overall efficiency and investment cost. The characteristics of all other conventional plants (using oil, natural gas or bioenergy) are described in the investment differences for desulphurisation, fuel handling and efficiency.<br /> *For Combined Cycle (CC) power plants, the characteristics of a natural gas fired plant are set as the standard. Other CC plants (fuelled by oil, bioenergy and coal after gasification) are defined by indicating additional capital costs for gasification, efficiency losses due to gasification, and operation and maintenance (O&amp;M) costs for fuel handling. <br /> *Power plants with carbon-capture-and-storage systems (CCS) are assumed to be CC plants, but with fuel-specific lower efficiency and higher investment and O&amp;M costs (related to capture and storage). <br /> *The characteristics of combined-heat-and-power plants (CHP) are similar to those of other plants, but with an assumed small increase in capital costs, in combination with a lower efficiency for electric conversion and an added factor for heat efficiency. <br /> <br /> The cost of one unit electricity generated is equal to the sum of the capital cost, operational and maintenance costs (O&amp;M), fuel cost, and CO2 storage cost.<br /> <br /> ===Solar and wind power===<br /> <br /> The costs of solar and wind power in the model are determined by learning and depletion dynamics. For renewable energy, costs relate to capital, O&amp;M and system integration. The capital costs mostly relate to learning and depletion processes. Learning is represented by in learning curves (Box 4.1.3.1); depletion is by long-term in cost–supply curves. <br /> <br /> The additional system integration costs relate to curtailed electricity (if production exceeds demand and the overcapacity cannot be used within the system), backup capacity; and additional required spinning reserve. The last items are needed to avoid loss of power if the supply of wind or solar power drops suddenly, enabling a power scale up in a relatively short time, in power stations operating below maximum capacity ([[Hoogwijk, 2004]]).<br /> <br /> To determine curtailed electricity, the model compares 10 points on the load-demand curve at the overlap between demand and supply. For both wind and solar power, a typical load supply curve is assumed (see [[Hoogwijk, 2004]]). If supply exceeds demand, the overcapacity in electricity is assumed to be discarded, resulting in higher production costs.<br /> <br /> Because wind and solar power supply is intermittent (variable and thus not reliable), the model assumes that backup capacity needs to be installed. It is assumed that no backup is required for first 5% penetration of the intermittent capacity. However, for higher levels of penetration, the effective capacity (degree to which operators can rely on plants producing at a specific time) of intermittent resources is assumed to decrease. This is referred to as the capacity factor. This decrease leads to the need for backup power by low-cost options, such as gas turbines, the cost of which is allocated to the intermittent source.<br /> <br /> The required spinning reserve of the power system is the capacity that can be used to respond to a rapid increase in demand. This is assumed to be 3.5% of the installed capacity of a conventional power plant. If wind and solar power further penetrate the market, the model assumes an additional, required spinning reserve of 15% of the intermittent capacity (after subtraction of the 3.5% existing capacity). The related costs are allocated to the intermittent source.<br /> <br /> <br /> {{FormulaAndTableTemplate|Formula1_ED}}<br /> <br /> The costs of solar and wind power are the model determined by learning and depletion dynamics. For renewable energy, costs relate to capital, O&amp;M and system integration. The capital costs mostly relate to [[Energy conversion/Description/Technical learning|learning]] and depletion processes (learning is represented by so-called learning curves; depletion is represented by long-term cost–supply curves). <br /> <br /> The additional system integration costs relate to <br /> # Discarded electricity in cases where production exceeds demand and the overcapacity cannot be used within the system;<br /> # Back-up capacity;<br /> # Additional required spinning reserve;<br /> The two last items are needed to avoid loss of power if the supply of wind or solar power suddenly drops, enabling a power scale up in a relatively short time, in power stations operating below maximum capacity ([[Hoogwijk, 2004]]).<br /> *To determine discarded electricity, the model makes a comparison between 10 different points on the load-demand curve, at the overlap between demand and supply. For both wind and solar power, a typical load–supply curve is assumed (see [[Hoogwijk, 2004]]). If supply exceeds demand, the overcapacity in electricity is assumed to be discarded, resulting in higher production costs. <br /> *Because wind and solar power supply is intermittent (i.e. it varies and therefore is not reliable), the model assumes that so-called back-up capacity needs to be installed. For the first 5% penetration of the intermittent capacity, it is assumed that no-back is required. However, for higher levels of penetration, the effective capacity (i.e. degree to which operators can rely on plants producing at a particular moment in time) of intermittent resources is assumed to decrease (referred to as the capacity factor). This decrease leads to the need of back-up power(by low-cost options, such as gas turbines), the costs of which are allocated to the intermittent source.<br /> *The required spinning reserve of the power system (capacity that can be used to respond to a rapid increase in demand) is assumed to be 3.5% of the installed capacity of a conventional power plant. If wind and solar power further penetrate the market, the model assumes an additional, required spinning reserve of 15% of the intermittent capacity (but after first subtracting the 3.5% existing capacity). The related costs are allocated to the intermittent source.<br /> <br /> ==Nuclear power==<br /> For nuclear power, the costs also consists of capital, O&amp;M and nuclear fuel costs. Similar to the renewable energy options, technology improvement nuclear power is described via a learning curve (so costs decrease with cumulative installed capacity). At the same time, fuel costs increase as a function of depletion. Fuel costs are determined on the basis of the estimated extraction costs of uranium and thorium resources, as is described in the component [[Energy supply]]. A small trade model for these fission fuels is included.<br /> <br /> ==Hydrogen generation model==<br /> The structure of the hydrogen model is similar to that of the electric power model ([[Van Ruijven et al., 2007]]). There are, however, some important differences:<br /> *The hydrogen model distinguishes the following 11 supply options: hydrogen production plants on the basis of coal, oil, natural gas and bio-energy, with and <br /> without carbon capture and storage (8 plants), hydrogen production from electrolysis, direct hydrogen production from solar thermal processes, and, finally, small methane reform plants. <br /> *For simplification, no description of preferences for different power plants is accounted for in the operational strategy. In other words, the load factor for each option equals the total production divided by the capacity for each region.<br /> *Intermittence does not play an important role, as hydrogen can be stored to some degree. Therefore, there are no equations simulating system integration.<br /> *Hydrogen can be traded. Therefore, a trade model is added, similar to the trade models for fossil fuels, as is described in the [[Energy supply]] section.<br /> <br /> &lt;references/&gt;<br /> }}<br /> s such as [[TIMER model|TIMER]] concentrate on introducing a set of simplified, meta relationships ([[Hoogwijk, 2004]]; [[Van Vuuren, 2007]]).<br /> <br /> ===Total demand for new capacity===<br /> The electricity capacity required to meet the demand per region is based on a forecast of the maximum electricity demand plus a reserve margin of about 10% (including the capacity credit assigned to different forms of electricity generation). Maximum demand is calculated on the basis of an assumed monthly shape of the load duration curve (LDC) and the gross electricity demand. The latter comprises the net electricity demand from the end-use sectors plus electricity trade and transmission losses ({{AbbrTemplate|LDC}}) accounts for characteristics such as cooling and lighting demand). The demand for new generation capacity is the difference between the required and existing capacity. Power plants are assumed to be replaced at the end of their lifetime, which varies from 30 to 50 years, depending on the technology and is currently fixed in the model.<br /> <br /> ===Decisions to invest in specific options ===<br /> In the following step, a decision is made to invest in different generation technologies. In the model, this is done on the basis of the price of electricity (in {{AbbrTemplate|USD/kWhe}} produced per technology, using a multinomial logit equation that assigns larger market shares to the lower cost options. The specific costs of each option is broken down into a number of categories: investment or capital costs (USD/kWe), fuel costs ([[HasAcronym::USD/GJ]]), operational and maintenance costs (OM) and other costs (see further). An exception is hydropower capacity, which is exogenously prescribed, because large hydropower plants often have functions other than only electricity production (e.g. water supply and flood control). In the equations, some constraints are added to account for limitations in supply (e.g. restrictions on biomass availability). The investments needed for each option are given in the form of total investment in new generation capacity and the share of each individual technology (determined on the basis of price and preference).<br /> <br /> ===Operational strategy===<br /> Use of power plants is based on operational costs, with low-cost technologies assumed to be used most often. This implies that capital-intensive plants with low operational costs, such as renewable and nuclear energy, operate as many hours as possible. To some degree, this is also true for other plants with low operational costs, such as coal. <br /> The operational decision is presented in the following three steps:<br /> #Renewable sources PV and wind are assigned, followed by hydropower, because these options have the lowest operational costs;<br /> #The peak load capacity (period of high electricity demand) is assigned on the basis of the operational costs of each available plant and the ability of these plants to provide peak load capacity; <br /> #Base load (period of medium to low energy demand) is assigned on the basis of the remaining capacity (after steps 1 and 2), operational costs and the ability of options to provide the base load capacity.<br /> <br /> <br /> ===Fossil-fuel and bio-energy power plants===<br /> A total of 20 types of power plants generating electricity using fossil fuels and bioenergy are included. These power plants represent different combinations of conventional technology, such as gasification and combined cycle (CC) technology; combined heat and power (CHP); and carbon capture and storage (CCS;(Hendriks et al., 2004b). The specific capital costs and thermal efficiencies of these types of plants are determined by exogenous assumptions that describe the technological progress of typical components of these plants:<br /> *For conventional power plants, the coal-fired plant is defined in terms of overall efficiency and investment cost. The characteristics of all other conventional plants (using oil, natural gas or bioenergy) are described in the investment differences for desulphurisation, fuel handling and efficiency.<br /> *For Combined Cycle (CC) power plants, the characteristics of a natural gas fired plant are set as the standard. Other CC plants (fuelled by oil, bioenergy and coal after gasification) are defined by indicating additional capital costs for gasification, efficiency losses due to gasification, and operation and maintenance (O&amp;M) costs for fuel handling. <br /> *Power plants with carbon-capture-and-storage systems (CCS) are assumed to be CC plants, but with fuel-specific lower efficiency and higher investment and O&amp;M costs (related to capture and storage). <br /> *The characteristics of combined-heat-and-power plants (CHP) are similar to those of other plants, but with an assumed small increase in capital costs, in combination with a lower efficiency for electric conversion and an added factor for heat efficiency. <br /> <br /> The cost of one unit electricity generated is equal to the sum of the capital cost, operational and maintenance costs (O&amp;M), fuel cost, and CO2 storage cost.<br /> <br /> ===Solar and wind power===<br /> <br /> The costs of solar and wind power in the model are determined by learning and depletion dynamics. For renewable energy, costs relate to capital, O&amp;M and system integration. The capital costs mostly relate to learning and depletion processes. Learning is represented by in learning curves (Box 4.1.3.1); depletion is by long-term in cost–supply curves. <br /> <br /> The additional system integration costs relate to curtailed electricity (if production exceeds demand and the overcapacity cannot be used within the system), backup capacity; and additional required spinning reserve. The last items are needed to avoid loss of power if the supply of wind or solar power drops suddenly, enabling a power scale up in a relatively short time, in power stations operating below maximum capacity ([[Hoogwijk, 2004]]).<br /> <br /> To determine curtailed electricity, the model compares 10 points on the load-demand curve at the overlap between demand and supply. For both wind and solar power, a typical load supply curve is assumed (see [[Hoogwijk, 2004]]). If supply exceeds demand, the overcapacity in electricity is assumed to be discarded, resulting in higher production costs.<br /> <br /> Because wind and solar power supply is intermittent (variable and thus not reliable), the model assumes that backup capacity needs to be installed. It is assumed that no backup is required for first 5% penetration of the intermittent capacity. However, for higher levels of penetration, the effective capacity (degree to which operators can rely on plants producing at a specific time) of intermittent resources is assumed to decrease. This is referred to as the capacity factor. This decrease leads to the need for backup power by low-cost options, such as gas turbines, the cost of which is allocated to the intermittent source.<br /> <br /> The required spinning reserve of the power system is the capacity that can be used to respond to a rapid increase in demand. This is assumed to be 3.5% of the installed capacity of a conventional power plant. If wind and solar power further penetrate the market, the model assumes an additional, required spinning reserve of 15% of the intermittent capacity (after subtraction of the 3.5% existing capacity). The related costs are allocated to the intermittent source.<br /> <br /> <br /> {{FormulaAndTableTemplate|Formula1_ED}}<br /> <br /> The costs of solar and wind power are the model determined by learning and depletion dynamics. For renewable energy, costs relate to capital, O&amp;M and system integration. The capital costs mostly relate to [[Energy conversion/Description/Technical learning|learning]] and depletion processes (learning is represented by so-called learning curves; depletion is represented by long-term cost–supply curves). <br /> <br /> The additional system integration costs relate to <br /> # Discarded electricity in cases where production exceeds demand and the overcapacity cannot be used within the system;<br /> # Back-up capacity;<br /> # Additional required spinning reserve;<br /> The two last items are needed to avoid loss of power if the supply of wind or solar power suddenly drops, enabling a power scale up in a relatively short time, in power stations operating below maximum capacity ([[Hoogwijk, 2004]]).<br /> *To determine discarded electricity, the model makes a comparison between 10 different points on the load-demand curve, at the overlap between demand and supply. For both wind and solar power, a typical load–supply curve is assumed (see [[Hoogwijk, 2004]]). If supply exceeds demand, the overcapacity in electricity is assumed to be discarded, resulting in higher production costs. <br /> *Because wind and solar power supply is intermittent (i.e. it varies and therefore is not reliable), the model assumes that so-called back-up capacity needs to be installed. For the first 5% penetration of the intermittent capacity, it is assumed that no-back is required. However, for higher levels of penetration, the effective capacity (i.e. degree to which operators can rely on plants producing at a particular moment in time) of intermittent resources is assumed to decrease (referred to as the capacity factor). This decrease leads to the need of back-up power(by low-cost options, such as gas turbines), the costs of which are allocated to the intermittent source.<br /> *The required spinning reserve of the power system (capacity that can be used to respond to a rapid increase in demand) is assumed to be 3.5% of the installed capacity of a conventional power plant. If wind and solar power further penetrate the market, the model assumes an additional, required spinning reserve of 15% of the intermittent capacity (but after first subtracting the 3.5% existing capacity). The related costs are allocated to the intermittent source.<br /> <br /> ==Nuclear power==<br /> For nuclear power, the costs also consists of capital, O&amp;M and nuclear fuel costs. Similar to the renewable energy options, technology improvement nuclear power is described via a learning curve (so costs decrease with cumulative installed capacity). At the same time, fuel costs increase as a function of depletion. Fuel costs are determined on the basis of the estimated extraction costs of uranium and thorium resources, as is described in the component [[Energy supply]]. A small trade model for these fission fuels is included.<br /> <br /> ==Hydrogen generation model==<br /> The structure of the hydrogen model is similar to that of the electric power model ([[Van Ruijven et al., 2007]]). There are, however, some important differences:<br /> *The hydrogen model distinguishes the following 11 supply options: hydrogen production plants on the basis of coal, oil, natural gas and bio-energy, with and <br /> without carbon capture and storage (8 plants), hydrogen production from electrolysis, direct hydrogen production from solar thermal processes, and, finally, small methane reform plants. <br /> *For simplification, no description of preferences for different power plants is accounted for in the operational strategy. In other words, the load factor for each option equals the total production divided by the capacity for each region.<br /> *Intermittence does not play an important role, as hydrogen can be stored to some degree. Therefore, there are no equations simulating system integration.<br /> *Hydrogen can be traded. Therefore, a trade model is added, similar to the trade models for fossil fuels, as is described in the [[Energy supply]] section.<br /> <br /> &lt;references/&gt;<br /> }}</div>

JoeriOostenrijk https://models.pbl.nl/index.php?title=Energy_conversion/Description&diff=21510 2014-05-08T15:52:12Z

<p>JoeriOostenrijk: </p> <hr /> <div>{{ComponentDescriptionTemplate<br /> |Reference=Hoogwijk, 2004; Van Vuuren, 2007; Hendriks et al., 2004b; Van Ruijven et al., 2007;<br /> |Description=[[TIMER model|TIMER]] includes two main energy conversion modules: Electric power generation and hydrogen generation. Below, electric power generation is described in detail. In addition, the key characteristics of the hydrogen generation model, which follows a similar structure, are presented.<br /> <br /> ==Electric power generation==<br /> As shown in the flowchart, two key elements of the electric power generation are the investment strategy and the operational strategy in the sector. A challenge in simulating electricity production in an aggregated model is that in reality electricity production depends on a range of complex factors, related to costs, reliance, and the time required to switch on technologies. Modelling these factors requires a high level of detail and thus {{AbbrTemplate|IAM}}s such as [[TIMER model|TIMER]] concentrate on introducing a set of simplified, meta relationships ([[Hoogwijk, 2004]]; [[Van Vuuren, 2007]]).<br /> <br /> ===Total demand for new capacity===<br /> The electricity capacity required to meet the demand per region is based on a forecast of the maximum electricity demand plus a reserve margin of about 10% (including the capacity credit assigned to different forms of electricity generation). Maximum demand is calculated on the basis of an assumed monthly shape of the load duration curve (LDC) and the gross electricity demand. The latter comprises the net electricity demand from the end-use sectors plus electricity trade and transmission losses ({{AbbrTemplate|LDC}}) accounts for characteristics such as cooling and lighting demand). The demand for new generation capacity is the difference between the required and existing capacity. Power plants are assumed to be replaced at the end of their lifetime, which varies from 30 to 50 years, depending on the technology and is currently fixed in the model.<br /> <br /> ===Decisions to invest in specific options ===<br /> In the following step, a decision is made to invest in different generation technologies. In the model, this is done on the basis of the price of electricity (in {{AbbrTemplate|USD/kWhe}} produced per technology, using a multinomial logit equation that assigns larger market shares to the lower cost options. The specific costs of each option is broken down into a number of categories: investment or capital costs (USD/kWe), fuel costs ([[HasAcronym::USD/GJ]]), operational and maintenance costs (OM) and other costs (see further). An exception is hydropower capacity, which is exogenously prescribed, because large hydropower plants often have functions other than only electricity production (e.g. water supply and flood control). In the equations, some constraints are added to account for limitations in supply (e.g. restrictions on biomass availability). The investments needed for each option are given in the form of total investment in new generation capacity and the share of each individual technology (determined on the basis of price and preference).<br /> <br /> ===Operational strategy===<br /> Use of power plants is based on operational costs, with low-cost technologies assumed to be used most often. This implies that capital-intensive plants with low operational costs, such as renewable and nuclear energy, operate as many hours as possible. To some degree, this is also true for other plants with low operational costs, such as coal. <br /> The operational decision is presented in the following three steps:<br /> #Renewable sources PV and wind are assigned, followed by hydropower, because these options have the lowest operational costs;<br /> #The peak load capacity (period of high electricity demand) is assigned on the basis of the operational costs of each available plant and the ability of these plants to provide peak load capacity; <br /> #Base load (period of medium to low energy demand) is assigned on the basis of the remaining capacity (after steps 1 and 2), operational costs and the ability of options to provide the base load capacity.<br /> <br /> <br /> ===Fossil-fuel and bio-energy power plants===<br /> A total of 20 types of power plants generating electricity using fossil fuels and bioenergy are included. These power plants represent different combinations of conventional technology, such as gasification and combined cycle (CC) technology; combined heat and power (CHP); and carbon capture and storage (CCS;(Hendriks et al., 2004b). The specific capital costs and thermal efficiencies of these types of plants are determined by exogenous assumptions that describe the technological progress of typical components of these plants:<br /> *For conventional power plants, the coal-fired plant is defined in terms of overall efficiency and investment cost. The characteristics of all other conventional plants (using oil, natural gas or bioenergy) are described in the investment differences for desulphurisation, fuel handling and efficiency.<br /> *For Combined Cycle (CC) power plants, the characteristics of a natural gas fired plant are set as the standard. Other CC plants (fuelled by oil, bioenergy and coal after gasification) are defined by indicating additional capital costs for gasification, efficiency losses due to gasification, and operation and maintenance (O&amp;M) costs for fuel handling. <br /> *Power plants with carbon-capture-and-storage systems (CCS) are assumed to be CC plants, but with fuel-specific lower efficiency and higher investment and O&amp;M costs (related to capture and storage). <br /> *The characteristics of combined-heat-and-power plants (CHP) are similar to those of other plants, but with an assumed small increase in capital costs, in combination with a lower efficiency for electric conversion and an added factor for heat efficiency. <br /> <br /> The cost of one unit electricity generated is equal to the sum of the capital cost, operational and maintenance costs (O&amp;M), fuel cost, and CO2 storage cost.<br /> <br /> ===Solar and wind power===<br /> <br /> The costs of solar and wind power in the model are determined by learning and depletion dynamics. For renewable energy, costs relate to capital, O&amp;M and system integration. The capital costs mostly relate to learning and depletion processes. Learning is represented by in learning curves (Box 4.1.3.1); depletion is by long-term in cost–supply curves. <br /> <br /> The additional system integration costs relate to curtailed electricity (if production exceeds demand and the overcapacity cannot be used within the system), backup capacity; and additional required spinning reserve. The last items are needed to avoid loss of power if the supply of wind or solar power drops suddenly, enabling a power scale up in a relatively short time, in power stations operating below maximum capacity ([[Hoogwijk, 2004]]).<br /> <br /> To determine curtailed electricity, the model compares 10 points on the load-demand curve at the overlap between demand and supply. For both wind and solar power, a typical load supply curve is assumed (see [[Hoogwijk, 2004]]). If supply exceeds demand, the overcapacity in electricity is assumed to be discarded, resulting in higher production costs.<br /> <br /> Because wind and solar power supply is intermittent (variable and thus not reliable), the model assumes that backup capacity needs to be installed. It is assumed that no backup is required for first 5% penetration of the intermittent capacity. However, for higher levels of penetration, the effective capacity (degree to which operators can rely on plants producing at a specific time) of intermittent resources is assumed to decrease. This is referred to as the capacity factor. This decrease leads to the need for backup power by low-cost options, such as gas turbines, the cost of which is allocated to the intermittent source.<br /> <br /> The required spinning reserve of the power system is the capacity that can be used to respond to a rapid increase in demand. This is assumed to be 3.5% of the installed capacity of a conventional power plant. If wind and solar power further penetrate the market, the model assumes an additional, required spinning reserve of 15% of the intermittent capacity (after subtraction of the 3.5% existing capacity). The related costs are allocated to the intermittent source.<br /> <br /> <br /> {{FormulaAndTableTemplate|Formula1_ED}}<br /> <br /> The costs of solar and wind power are the model determined by learning and depletion dynamics. For renewable energy, costs relate to capital, O&amp;M and system integration. The capital costs mostly relate to [[Energy conversion/Description/Technical learning|learning]] and depletion processes (learning is represented by so-called learning curves; depletion is represented by long-term cost–supply curves). <br /> <br /> The additional system integration costs relate to <br /> # Discarded electricity in cases where production exceeds demand and the overcapacity cannot be used within the system;<br /> # Back-up capacity;<br /> # Additional required spinning reserve;<br /> The two last items are needed to avoid loss of power if the supply of wind or solar power suddenly drops, enabling a power scale up in a relatively short time, in power stations operating below maximum capacity ([[Hoogwijk, 2004]]).<br /> *To determine discarded electricity, the model makes a comparison between 10 different points on the load-demand curve, at the overlap between demand and supply. For both wind and solar power, a typical load–supply curve is assumed (see [[Hoogwijk, 2004]]). If supply exceeds demand, the overcapacity in electricity is assumed to be discarded, resulting in higher production costs. <br /> *Because wind and solar power supply is intermittent (i.e. it varies and therefore is not reliable), the model assumes that so-called back-up capacity needs to be installed. For the first 5% penetration of the intermittent capacity, it is assumed that no-back is required. However, for higher levels of penetration, the effective capacity (i.e. degree to which operators can rely on plants producing at a particular moment in time) of intermittent resources is assumed to decrease (referred to as the capacity factor). This decrease leads to the need of back-up power(by low-cost options, such as gas turbines), the costs of which are allocated to the intermittent source.<br /> *The required spinning reserve of the power system (capacity that can be used to respond to a rapid increase in demand) is assumed to be 3.5% of the installed capacity of a conventional power plant. If wind and solar power further penetrate the market, the model assumes an additional, required spinning reserve of 15% of the intermittent capacity (but after first subtracting the 3.5% existing capacity). The related costs are allocated to the intermittent source.<br /> <br /> ==Nuclear power==<br /> For nuclear power, the costs also consists of capital, O&amp;M and nuclear fuel costs. Similar to the renewable energy options, technology improvement nuclear power is described via a learning curve (so costs decrease with cumulative installed capacity). At the same time, fuel costs increase as a function of depletion. Fuel costs are determined on the basis of the estimated extraction costs of uranium and thorium resources, as is described in the component [[Energy supply]]. A small trade model for these fission fuels is included.<br /> <br /> ==Hydrogen generation model==<br /> The structure of the hydrogen model is similar to that of the electric power model ([[Van Ruijven et al., 2007]]). There are, however, some important differences:<br /> *The hydrogen model distinguishes the following 11 supply options: hydrogen production plants on the basis of coal, oil, natural gas and bio-energy, with and <br /> without carbon capture and storage (8 plants), hydrogen production from electrolysis, direct hydrogen production from solar thermal processes, and, finally, small methane reform plants. <br /> *For simplification, no description of preferences for different power plants is accounted for in the operational strategy. In other words, the load factor for each option equals the total production divided by the capacity for each region.<br /> *Intermittence does not play an important role, as hydrogen can be stored to some degree. Therefore, there are no equations simulating system integration.<br /> *Hydrogen can be traded. Therefore, a trade model is added, similar to the trade models for fossil fuels, as is described in the [[Energy supply]] section.<br /> <br /> &lt;references/&gt;<br /> }}<br /> s such as [[TIMER model|TIMER]] concentrate on introducing a set of simplified, meta relationships ([[Hoogwijk, 2004]]; [[Van Vuuren, 2007]]).<br /> <br /> ===Total demand for new capacity===<br /> The electricity capacity required to meet the demand per region is based on a forecast of the maximum electricity demand plus a reserve margin of about 10% (including the capacity credit assigned to different forms of electricity generation). Maximum demand is calculated on the basis of an assumed monthly shape of the load duration curve (LDC) and the gross electricity demand. The latter comprises the net electricity demand from the end-use sectors plus electricity trade and transmission losses ({{AbbrTemplate|LDC}}) accounts for characteristics such as cooling and lighting demand). The demand for new generation capacity is the difference between the required and existing capacity. Power plants are assumed to be replaced at the end of their lifetime, which varies from 30 to 50 years, depending on the technology and is currently fixed in the model.<br /> <br /> ===Decisions to invest in specific options ===<br /> In the following step, a decision is made to invest in different generation technologies. In the model, this is done on the basis of the price of electricity (in {{AbbrTemplate|USD/kWhe}} produced per technology, using a multinomial logit equation that assigns larger market shares to the lower cost options. The specific costs of each option is broken down into a number of categories: investment or capital costs (USD/kWe), fuel costs ([[HasAcronym::USD/GJ]]), operational and maintenance costs (OM) and other costs (see further). An exception is hydropower capacity, which is exogenously prescribed, because large hydropower plants often have functions other than only electricity production (e.g. water supply and flood control). In the equations, some constraints are added to account for limitations in supply (e.g. restrictions on biomass availability). The investments needed for each option are given in the form of total investment in new generation capacity and the share of each individual technology (determined on the basis of price and preference).<br /> <br /> ===Operational strategy===<br /> Use of power plants is based on operational costs, with low-cost technologies assumed to be used most often. This implies that capital-intensive plants with low operational costs, such as renewable and nuclear energy, operate as many hours as possible. To some degree, this is also true for other plants with low operational costs, such as coal. <br /> The operational decision is presented in the following three steps:<br /> #Renewable sources PV and wind are assigned, followed by hydropower, because these options have the lowest operational costs;<br /> #The peak load capacity (period of high electricity demand) is assigned on the basis of the operational costs of each available plant and the ability of these plants to provide peak load capacity; <br /> #Base load (period of medium to low energy demand) is assigned on the basis of the remaining capacity (after steps 1 and 2), operational costs and the ability of options to provide the base load capacity.<br /> <br /> <br /> ===Fossil-fuel and bio-energy power plants===<br /> A total of 20 types of power plants generating electricity using fossil fuels and bioenergy are included. These power plants represent different combinations of conventional technology, such as gasification and combined cycle (CC) technology; combined heat and power (CHP); and carbon capture and storage (CCS;(Hendriks et al., 2004b). The specific capital costs and thermal efficiencies of these types of plants are determined by exogenous assumptions that describe the technological progress of typical components of these plants:<br /> *For conventional power plants, the coal-fired plant is defined in terms of overall efficiency and investment cost. The characteristics of all other conventional plants (using oil, natural gas or bioenergy) are described in the investment differences for desulphurisation, fuel handling and efficiency.<br /> *For Combined Cycle (CC) power plants, the characteristics of a natural gas fired plant are set as the standard. Other CC plants (fuelled by oil, bioenergy and coal after gasification) are defined by indicating additional capital costs for gasification, efficiency losses due to gasification, and operation and maintenance (O&amp;M) costs for fuel handling. <br /> *Power plants with carbon-capture-and-storage systems (CCS) are assumed to be CC plants, but with fuel-specific lower efficiency and higher investment and O&amp;M costs (related to capture and storage). <br /> *The characteristics of combined-heat-and-power plants (CHP) are similar to those of other plants, but with an assumed small increase in capital costs, in combination with a lower efficiency for electric conversion and an added factor for heat efficiency. <br /> <br /> The cost of one unit electricity generated is equal to the sum of the capital cost, operational and maintenance costs (O&amp;M), fuel cost, and CO2 storage cost.<br /> <br /> ===Solar and wind power===<br /> <br /> The costs of solar and wind power in the model are determined by learning and depletion dynamics. For renewable energy, costs relate to capital, O&amp;M and system integration. The capital costs mostly relate to learning and depletion processes. Learning is represented by in learning curves (Box 4.1.3.1); depletion is by long-term in cost–supply curves. <br /> <br /> The additional system integration costs relate to curtailed electricity (if production exceeds demand and the overcapacity cannot be used within the system), backup capacity; and additional required spinning reserve. The last items are needed to avoid loss of power if the supply of wind or solar power drops suddenly, enabling a power scale up in a relatively short time, in power stations operating below maximum capacity ([[Hoogwijk, 2004]]).<br /> <br /> To determine curtailed electricity, the model compares 10 points on the load-demand curve at the overlap between demand and supply. For both wind and solar power, a typical load supply curve is assumed (see [[Hoogwijk, 2004]]). If supply exceeds demand, the overcapacity in electricity is assumed to be discarded, resulting in higher production costs.<br /> <br /> Because wind and solar power supply is intermittent (variable and thus not reliable), the model assumes that backup capacity needs to be installed. It is assumed that no backup is required for first 5% penetration of the intermittent capacity. However, for higher levels of penetration, the effective capacity (degree to which operators can rely on plants producing at a specific time) of intermittent resources is assumed to decrease. This is referred to as the capacity factor. This decrease leads to the need for backup power by low-cost options, such as gas turbines, the cost of which is allocated to the intermittent source.<br /> <br /> The required spinning reserve of the power system is the capacity that can be used to respond to a rapid increase in demand. This is assumed to be 3.5% of the installed capacity of a conventional power plant. If wind and solar power further penetrate the market, the model assumes an additional, required spinning reserve of 15% of the intermittent capacity (after subtraction of the 3.5% existing capacity). The related costs are allocated to the intermittent source.<br /> <br /> <br /> {{FormulaAndTableTemplate|Formula1_ED}}<br /> <br /> The costs of solar and wind power are the model determined by learning and depletion dynamics. For renewable energy, costs relate to capital, O&amp;M and system integration. The capital costs mostly relate to [[Energy conversion/Description/Technical learning|learning]] and depletion processes (learning is represented by so-called learning curves; depletion is represented by long-term cost–supply curves). <br /> <br /> The additional system integration costs relate to <br /> # Discarded electricity in cases where production exceeds demand and the overcapacity cannot be used within the system;<br /> # Back-up capacity;<br /> # Additional required spinning reserve;<br /> The two last items are needed to avoid loss of power if the supply of wind or solar power suddenly drops, enabling a power scale up in a relatively short time, in power stations operating below maximum capacity ([[Hoogwijk, 2004]]).<br /> *To determine discarded electricity, the model makes a comparison between 10 different points on the load-demand curve, at the overlap between demand and supply. For both wind and solar power, a typical load–supply curve is assumed (see [[Hoogwijk, 2004]]). If supply exceeds demand, the overcapacity in electricity is assumed to be discarded, resulting in higher production costs. <br /> *Because wind and solar power supply is intermittent (i.e. it varies and therefore is not reliable), the model assumes that so-called back-up capacity needs to be installed. For the first 5% penetration of the intermittent capacity, it is assumed that no-back is required. However, for higher levels of penetration, the effective capacity (i.e. degree to which operators can rely on plants producing at a particular moment in time) of intermittent resources is assumed to decrease (referred to as the capacity factor). This decrease leads to the need of back-up power(by low-cost options, such as gas turbines), the costs of which are allocated to the intermittent source.<br /> *The required spinning reserve of the power system (capacity that can be used to respond to a rapid increase in demand) is assumed to be 3.5% of the installed capacity of a conventional power plant. If wind and solar power further penetrate the market, the model assumes an additional, required spinning reserve of 15% of the intermittent capacity (but after first subtracting the 3.5% existing capacity). The related costs are allocated to the intermittent source.<br /> <br /> ==Nuclear power==<br /> For nuclear power, the costs also consists of capital, O&amp;M and nuclear fuel costs. Similar to the renewable energy options, technology improvement nuclear power is described via a learning curve (so costs decrease with cumulative installed capacity). At the same time, fuel costs increase as a function of depletion. Fuel costs are determined on the basis of the estimated extraction costs of uranium and thorium resources, as is described in the component [[Energy supply]]. A small trade model for these fission fuels is included.<br /> <br /> ==Hydrogen generation model==<br /> The structure of the hydrogen model is similar to that of the electric power model ([[Van Ruijven et al., 2007]]). There are, however, some important differences:<br /> *The hydrogen model distinguishes the following 11 supply options: hydrogen production plants on the basis of coal, oil, natural gas and bio-energy, with and <br /> without carbon capture and storage (8 plants), hydrogen production from electrolysis, direct hydrogen production from solar thermal processes, and, finally, small methane reform plants. <br /> *For simplification, no description of preferences for different power plants is accounted for in the operational strategy. In other words, the load factor for each option equals the total production divided by the capacity for each region.<br /> *Intermittence does not play an important role, as hydrogen can be stored to some degree. Therefore, there are no equations simulating system integration.<br /> *Hydrogen can be traded. Therefore, a trade model is added, similar to the trade models for fossil fuels, as is described in the [[Energy supply]] section.<br /> <br /> &lt;references/&gt;<br /> }}</div>

JoeriOostenrijk https://models.pbl.nl/index.php?title=Energy_conversion/Description&diff=21509 2014-05-08T15:51:45Z

<p>JoeriOostenrijk: </p> <hr /> <div>{{ComponentDescriptionTemplate<br /> |Reference=Hoogwijk, 2004; Van Vuuren, 2007; Hendriks et al., 2004b; Van Ruijven et al., 2007;<br /> |Description=[[TIMER model|TIMER]] includes two main energy conversion modules: Electric power generation and hydrogen generation. Below, electric power generation is described in detail. In addition, the key characteristics of the hydrogen generation model, which follows a similar structure, are presented.<br /> <br /> ==Electric power generation==<br /> As shown in the flowchart, two key elements of the electric power generation are the investment strategy and the operational strategy in the sector. A challenge in simulating electricity production in an aggregated model is that in reality electricity production depends on a range of complex factors, related to costs, reliance, and the time required to switch on technologies. Modelling these factors requires a high level of detail and thus {{AbbrTemplate|IAM}}}}s such as [[TIMER model|TIMER]] concentrate on introducing a set of simplified, meta relationships ([[Hoogwijk, 2004]]; [[Van Vuuren, 2007]]).<br /> <br /> ===Total demand for new capacity===<br /> The electricity capacity required to meet the demand per region is based on a forecast of the maximum electricity demand plus a reserve margin of about 10% (including the capacity credit assigned to different forms of electricity generation). Maximum demand is calculated on the basis of an assumed monthly shape of the load duration curve (LDC) and the gross electricity demand. The latter comprises the net electricity demand from the end-use sectors plus electricity trade and transmission losses ({{AbbrTemplate|LDC}}) accounts for characteristics such as cooling and lighting demand). The demand for new generation capacity is the difference between the required and existing capacity. Power plants are assumed to be replaced at the end of their lifetime, which varies from 30 to 50 years, depending on the technology and is currently fixed in the model.<br /> <br /> ===Decisions to invest in specific options ===<br /> In the following step, a decision is made to invest in different generation technologies. In the model, this is done on the basis of the price of electricity (in {{AbbrTemplate|USD/kWhe}} produced per technology, using a multinomial logit equation that assigns larger market shares to the lower cost options. The specific costs of each option is broken down into a number of categories: investment or capital costs (USD/kWe), fuel costs ([[HasAcronym::USD/GJ]]), operational and maintenance costs (OM) and other costs (see further). An exception is hydropower capacity, which is exogenously prescribed, because large hydropower plants often have functions other than only electricity production (e.g. water supply and flood control). In the equations, some constraints are added to account for limitations in supply (e.g. restrictions on biomass availability). The investments needed for each option are given in the form of total investment in new generation capacity and the share of each individual technology (determined on the basis of price and preference).<br /> <br /> ===Operational strategy===<br /> Use of power plants is based on operational costs, with low-cost technologies assumed to be used most often. This implies that capital-intensive plants with low operational costs, such as renewable and nuclear energy, operate as many hours as possible. To some degree, this is also true for other plants with low operational costs, such as coal. <br /> The operational decision is presented in the following three steps:<br /> #Renewable sources PV and wind are assigned, followed by hydropower, because these options have the lowest operational costs;<br /> #The peak load capacity (period of high electricity demand) is assigned on the basis of the operational costs of each available plant and the ability of these plants to provide peak load capacity; <br /> #Base load (period of medium to low energy demand) is assigned on the basis of the remaining capacity (after steps 1 and 2), operational costs and the ability of options to provide the base load capacity.<br /> <br /> <br /> ===Fossil-fuel and bio-energy power plants===<br /> A total of 20 types of power plants generating electricity using fossil fuels and bioenergy are included. These power plants represent different combinations of conventional technology, such as gasification and combined cycle (CC) technology; combined heat and power (CHP); and carbon capture and storage (CCS;(Hendriks et al., 2004b). The specific capital costs and thermal efficiencies of these types of plants are determined by exogenous assumptions that describe the technological progress of typical components of these plants:<br /> *For conventional power plants, the coal-fired plant is defined in terms of overall efficiency and investment cost. The characteristics of all other conventional plants (using oil, natural gas or bioenergy) are described in the investment differences for desulphurisation, fuel handling and efficiency.<br /> *For Combined Cycle (CC) power plants, the characteristics of a natural gas fired plant are set as the standard. Other CC plants (fuelled by oil, bioenergy and coal after gasification) are defined by indicating additional capital costs for gasification, efficiency losses due to gasification, and operation and maintenance (O&amp;M) costs for fuel handling. <br /> *Power plants with carbon-capture-and-storage systems (CCS) are assumed to be CC plants, but with fuel-specific lower efficiency and higher investment and O&amp;M costs (related to capture and storage). <br /> *The characteristics of combined-heat-and-power plants (CHP) are similar to those of other plants, but with an assumed small increase in capital costs, in combination with a lower efficiency for electric conversion and an added factor for heat efficiency. <br /> <br /> The cost of one unit electricity generated is equal to the sum of the capital cost, operational and maintenance costs (O&amp;M), fuel cost, and CO2 storage cost.<br /> <br /> ===Solar and wind power===<br /> <br /> The costs of solar and wind power in the model are determined by learning and depletion dynamics. For renewable energy, costs relate to capital, O&amp;M and system integration. The capital costs mostly relate to learning and depletion processes. Learning is represented by in learning curves (Box 4.1.3.1); depletion is by long-term in cost–supply curves. <br /> <br /> The additional system integration costs relate to curtailed electricity (if production exceeds demand and the overcapacity cannot be used within the system), backup capacity; and additional required spinning reserve. The last items are needed to avoid loss of power if the supply of wind or solar power drops suddenly, enabling a power scale up in a relatively short time, in power stations operating below maximum capacity ([[Hoogwijk, 2004]]).<br /> <br /> To determine curtailed electricity, the model compares 10 points on the load-demand curve at the overlap between demand and supply. For both wind and solar power, a typical load supply curve is assumed (see [[Hoogwijk, 2004]]). If supply exceeds demand, the overcapacity in electricity is assumed to be discarded, resulting in higher production costs.<br /> <br /> Because wind and solar power supply is intermittent (variable and thus not reliable), the model assumes that backup capacity needs to be installed. It is assumed that no backup is required for first 5% penetration of the intermittent capacity. However, for higher levels of penetration, the effective capacity (degree to which operators can rely on plants producing at a specific time) of intermittent resources is assumed to decrease. This is referred to as the capacity factor. This decrease leads to the need for backup power by low-cost options, such as gas turbines, the cost of which is allocated to the intermittent source.<br /> <br /> The required spinning reserve of the power system is the capacity that can be used to respond to a rapid increase in demand. This is assumed to be 3.5% of the installed capacity of a conventional power plant. If wind and solar power further penetrate the market, the model assumes an additional, required spinning reserve of 15% of the intermittent capacity (after subtraction of the 3.5% existing capacity). The related costs are allocated to the intermittent source.<br /> <br /> <br /> {{FormulaAndTableTemplate|Formula1_ED}}<br /> <br /> The costs of solar and wind power are the model determined by learning and depletion dynamics. For renewable energy, costs relate to capital, O&amp;M and system integration. The capital costs mostly relate to [[Energy conversion/Description/Technical learning|learning]] and depletion processes (learning is represented by so-called learning curves; depletion is represented by long-term cost–supply curves). <br /> <br /> The additional system integration costs relate to <br /> # Discarded electricity in cases where production exceeds demand and the overcapacity cannot be used within the system;<br /> # Back-up capacity;<br /> # Additional required spinning reserve;<br /> The two last items are needed to avoid loss of power if the supply of wind or solar power suddenly drops, enabling a power scale up in a relatively short time, in power stations operating below maximum capacity ([[Hoogwijk, 2004]]).<br /> *To determine discarded electricity, the model makes a comparison between 10 different points on the load-demand curve, at the overlap between demand and supply. For both wind and solar power, a typical load–supply curve is assumed (see [[Hoogwijk, 2004]]). If supply exceeds demand, the overcapacity in electricity is assumed to be discarded, resulting in higher production costs. <br /> *Because wind and solar power supply is intermittent (i.e. it varies and therefore is not reliable), the model assumes that so-called back-up capacity needs to be installed. For the first 5% penetration of the intermittent capacity, it is assumed that no-back is required. However, for higher levels of penetration, the effective capacity (i.e. degree to which operators can rely on plants producing at a particular moment in time) of intermittent resources is assumed to decrease (referred to as the capacity factor). This decrease leads to the need of back-up power(by low-cost options, such as gas turbines), the costs of which are allocated to the intermittent source.<br /> *The required spinning reserve of the power system (capacity that can be used to respond to a rapid increase in demand) is assumed to be 3.5% of the installed capacity of a conventional power plant. If wind and solar power further penetrate the market, the model assumes an additional, required spinning reserve of 15% of the intermittent capacity (but after first subtracting the 3.5% existing capacity). The related costs are allocated to the intermittent source.<br /> <br /> ==Nuclear power==<br /> For nuclear power, the costs also consists of capital, O&amp;M and nuclear fuel costs. Similar to the renewable energy options, technology improvement nuclear power is described via a learning curve (so costs decrease with cumulative installed capacity). At the same time, fuel costs increase as a function of depletion. Fuel costs are determined on the basis of the estimated extraction costs of uranium and thorium resources, as is described in the component [[Energy supply]]. A small trade model for these fission fuels is included.<br /> <br /> ==Hydrogen generation model==<br /> The structure of the hydrogen model is similar to that of the electric power model ([[Van Ruijven et al., 2007]]). There are, however, some important differences:<br /> *The hydrogen model distinguishes the following 11 supply options: hydrogen production plants on the basis of coal, oil, natural gas and bio-energy, with and <br /> without carbon capture and storage (8 plants), hydrogen production from electrolysis, direct hydrogen production from solar thermal processes, and, finally, small methane reform plants. <br /> *For simplification, no description of preferences for different power plants is accounted for in the operational strategy. In other words, the load factor for each option equals the total production divided by the capacity for each region.<br /> *Intermittence does not play an important role, as hydrogen can be stored to some degree. Therefore, there are no equations simulating system integration.<br /> *Hydrogen can be traded. Therefore, a trade model is added, similar to the trade models for fossil fuels, as is described in the [[Energy supply]] section.<br /> <br /> &lt;references/&gt;<br /> }}</div>

JoeriOostenrijk https://models.pbl.nl/index.php?title=Energy_conversion/Description&diff=21508 2014-05-08T15:49:16Z

<p>JoeriOostenrijk: </p> <hr /> <div>{{ComponentDescriptionTemplate<br /> |Reference=Hoogwijk, 2004; Van Vuuren, 2007; Hendriks et al., 2004b; Van Ruijven et al., 2007;<br /> |Description=[[TIMER model|TIMER]] includes two main energy conversion modules: Electric power generation and hydrogen generation. Below, electric power generation is described in detail. In addition, the key characteristics of the hydrogen generation model, which follows a similar structure, are presented.<br /> <br /> ==Electric power generation==<br /> As shown in the flowchart, two key elements of the electric power generation are the investment strategy and the operational strategy in the sector. A challenge in simulating electricity production in an aggregated model is that in reality electricity production depends on a range of complex factors, related to costs, reliance, and the time required to switch on technologies. Modelling these factors requires a high level of detail and thus {{AbbrTemplate|IAM}}s such as [[TIMER model|TIMER]] concentrate on introducing a set of simplified, meta relationships ([[Hoogwijk, 2004]]; [[Van Vuuren, 2007]]).<br /> <br /> ===Total demand for new capacity===<br /> The electricity capacity required to meet the demand per region is based on a forecast of the maximum electricity demand plus a reserve margin of about 10% (including the capacity credit assigned to different forms of electricity generation). Maximum demand is calculated on the basis of an assumed monthly shape of the load duration curve (LDC) and the gross electricity demand. The latter comprises the net electricity demand from the end-use sectors plus electricity trade and transmission losses ({{AbbrTemplate|LDC}}) accounts for characteristics such as cooling and lighting demand). The demand for new generation capacity is the difference between the required and existing capacity. Power plants are assumed to be replaced at the end of their lifetime, which varies from 30 to 50 years, depending on the technology and is currently fixed in the model.<br /> <br /> ===Decisions to invest in specific options ===<br /> In the following step, a decision is made to invest in different generation technologies. In the model, this is done on the basis of the price of electricity (in {{AbbrTemplate|USD/kWhe}} produced per technology, using a multinomial logit equation that assigns larger market shares to the lower cost options. The specific costs of each option is broken down into a number of categories: investment or capital costs (USD/kWe), fuel costs ([[HasAcronym::USD/GJ]]), operational and maintenance costs (OM) and other costs (see further). An exception is hydropower capacity, which is exogenously prescribed, because large hydropower plants often have functions other than only electricity production (e.g. water supply and flood control). In the equations, some constraints are added to account for limitations in supply (e.g. restrictions on biomass availability). The investments needed for each option are given in the form of total investment in new generation capacity and the share of each individual technology (determined on the basis of price and preference).<br /> <br /> ===Operational strategy===<br /> Use of power plants is based on operational costs, with low-cost technologies assumed to be used most often. This implies that capital-intensive plants with low operational costs, such as renewable and nuclear energy, operate as many hours as possible. To some degree, this is also true for other plants with low operational costs, such as coal. <br /> The operational decision is presented in the following three steps:<br /> #Renewable sources PV and wind are assigned, followed by hydropower, because these options have the lowest operational costs;<br /> #The peak load capacity (period of high electricity demand) is assigned on the basis of the operational costs of each available plant and the ability of these plants to provide peak load capacity; <br /> #Base load (period of medium to low energy demand) is assigned on the basis of the remaining capacity (after steps 1 and 2), operational costs and the ability of options to provide the base load capacity.<br /> <br /> <br /> ===Fossil-fuel and bio-energy power plants===<br /> A total of 20 types of power plants generating electricity using fossil fuels and bioenergy are included. These power plants represent different combinations of conventional technology, such as gasification and combined cycle (CC) technology; combined heat and power (CHP); and carbon capture and storage (CCS;(Hendriks et al., 2004b). The specific capital costs and thermal efficiencies of these types of plants are determined by exogenous assumptions that describe the technological progress of typical components of these plants:<br /> *For conventional power plants, the coal-fired plant is defined in terms of overall efficiency and investment cost. The characteristics of all other conventional plants (using oil, natural gas or bioenergy) are described in the investment differences for desulphurisation, fuel handling and efficiency.<br /> *For Combined Cycle (CC) power plants, the characteristics of a natural gas fired plant are set as the standard. Other CC plants (fuelled by oil, bioenergy and coal after gasification) are defined by indicating additional capital costs for gasification, efficiency losses due to gasification, and operation and maintenance (O&amp;M) costs for fuel handling. <br /> *Power plants with carbon-capture-and-storage systems (CCS) are assumed to be CC plants, but with fuel-specific lower efficiency and higher investment and O&amp;M costs (related to capture and storage). <br /> *The characteristics of combined-heat-and-power plants (CHP) are similar to those of other plants, but with an assumed small increase in capital costs, in combination with a lower efficiency for electric conversion and an added factor for heat efficiency. <br /> <br /> The cost of one unit electricity generated is equal to the sum of the capital cost, operational and maintenance costs (O&amp;M), fuel cost, and CO2 storage cost.<br /> <br /> ===Solar and wind power===<br /> <br /> The costs of solar and wind power in the model are determined by learning and depletion dynamics. For renewable energy, costs relate to capital, O&amp;M and system integration. The capital costs mostly relate to learning and depletion processes. Learning is represented by in learning curves (Box 4.1.3.1); depletion is by long-term in cost–supply curves. <br /> <br /> The additional system integration costs relate to curtailed electricity (if production exceeds demand and the overcapacity cannot be used within the system), backup capacity; and additional required spinning reserve. The last items are needed to avoid loss of power if the supply of wind or solar power drops suddenly, enabling a power scale up in a relatively short time, in power stations operating below maximum capacity ([[Hoogwijk, 2004]]).<br /> <br /> To determine curtailed electricity, the model compares 10 points on the load-demand curve at the overlap between demand and supply. For both wind and solar power, a typical load supply curve is assumed (see [[Hoogwijk, 2004]]). If supply exceeds demand, the overcapacity in electricity is assumed to be discarded, resulting in higher production costs.<br /> <br /> Because wind and solar power supply is intermittent (variable and thus not reliable), the model assumes that backup capacity needs to be installed. It is assumed that no backup is required for first 5% penetration of the intermittent capacity. However, for higher levels of penetration, the effective capacity (degree to which operators can rely on plants producing at a specific time) of intermittent resources is assumed to decrease. This is referred to as the capacity factor. This decrease leads to the need for backup power by low-cost options, such as gas turbines, the cost of which is allocated to the intermittent source.<br /> <br /> The required spinning reserve of the power system is the capacity that can be used to respond to a rapid increase in demand. This is assumed to be 3.5% of the installed capacity of a conventional power plant. If wind and solar power further penetrate the market, the model assumes an additional, required spinning reserve of 15% of the intermittent capacity (after subtraction of the 3.5% existing capacity). The related costs are allocated to the intermittent source.<br /> <br /> <br /> {{FormulaAndTableTemplate|Formula1_ED}}<br /> <br /> The costs of solar and wind power are the model determined by learning and depletion dynamics. For renewable energy, costs relate to capital, O&amp;M and system integration. The capital costs mostly relate to [[Energy conversion/Description/Technical learning|learning]] and depletion processes (learning is represented by so-called learning curves; depletion is represented by long-term cost–supply curves). <br /> <br /> The additional system integration costs relate to <br /> # Discarded electricity in cases where production exceeds demand and the overcapacity cannot be used within the system;<br /> # Back-up capacity;<br /> # Additional required spinning reserve;<br /> The two last items are needed to avoid loss of power if the supply of wind or solar power suddenly drops, enabling a power scale up in a relatively short time, in power stations operating below maximum capacity ([[Hoogwijk, 2004]]).<br /> *To determine discarded electricity, the model makes a comparison between 10 different points on the load-demand curve, at the overlap between demand and supply. For both wind and solar power, a typical load–supply curve is assumed (see [[Hoogwijk, 2004]]). If supply exceeds demand, the overcapacity in electricity is assumed to be discarded, resulting in higher production costs. <br /> *Because wind and solar power supply is intermittent (i.e. it varies and therefore is not reliable), the model assumes that so-called back-up capacity needs to be installed. For the first 5% penetration of the intermittent capacity, it is assumed that no-back is required. However, for higher levels of penetration, the effective capacity (i.e. degree to which operators can rely on plants producing at a particular moment in time) of intermittent resources is assumed to decrease (referred to as the capacity factor). This decrease leads to the need of back-up power(by low-cost options, such as gas turbines), the costs of which are allocated to the intermittent source.<br /> *The required spinning reserve of the power system (capacity that can be used to respond to a rapid increase in demand) is assumed to be 3.5% of the installed capacity of a conventional power plant. If wind and solar power further penetrate the market, the model assumes an additional, required spinning reserve of 15% of the intermittent capacity (but after first subtracting the 3.5% existing capacity). The related costs are allocated to the intermittent source.<br /> <br /> ==Nuclear power==<br /> For nuclear power, the costs also consists of capital, O&amp;M and nuclear fuel costs. Similar to the renewable energy options, technology improvement nuclear power is described via a learning curve (so costs decrease with cumulative installed capacity). At the same time, fuel costs increase as a function of depletion. Fuel costs are determined on the basis of the estimated extraction costs of uranium and thorium resources, as is described in the component [[Energy supply]]. A small trade model for these fission fuels is included.<br /> <br /> ==Hydrogen generation model==<br /> The structure of the hydrogen model is similar to that of the electric power model ([[Van Ruijven et al., 2007]]). There are, however, some important differences:<br /> *The hydrogen model distinguishes the following 11 supply options: hydrogen production plants on the basis of coal, oil, natural gas and bio-energy, with and <br /> without carbon capture and storage (8 plants), hydrogen production from electrolysis, direct hydrogen production from solar thermal processes, and, finally, small methane reform plants. <br /> *For simplification, no description of preferences for different power plants is accounted for in the operational strategy. In other words, the load factor for each option equals the total production divided by the capacity for each region.<br /> *Intermittence does not play an important role, as hydrogen can be stored to some degree. Therefore, there are no equations simulating system integration.<br /> *Hydrogen can be traded. Therefore, a trade model is added, similar to the trade models for fossil fuels, as is described in the [[Energy supply]] section.<br /> <br /> &lt;references/&gt;<br /> }}</div>

JoeriOostenrijk https://models.pbl.nl/index.php?title=Energy_conversion/Description&diff=21507 2014-05-08T15:48:36Z

<p>JoeriOostenrijk: </p> <hr /> <div>{{ComponentDescriptionTemplate<br /> |Reference=Hoogwijk, 2004; Van Vuuren, 2007; Hendriks et al., 2004b; Van Ruijven et al., 2007;<br /> |Description=[[TIMER model|TIMER]] includes two main energy conversion modules: Electric power generation and hydrogen generation. Below, electric power generation is described in detail. In addition, the key characteristics of the hydrogen generation model, which follows a similar structure, are presented.<br /> <br /> ==Electric power generation==<br /> As shown in the flowchart, two key elements of the electric power generation are the investment strategy and the operational strategy in the sector. A challenge in simulating electricity production in an aggregated model is that in reality electricity production depends on a range of complex factors, related to costs, reliance, and the time required to switch on technologies. Modelling these factors requires a high level of detail and thus {{AbbrTemplate|IAM}}s such as [[TIMER model|TIMER]] concentrate on introducing a set of simplified, meta relationships ([[Hoogwijk, 2004]]; [[Van Vuuren, 2007]]).<br /> <br /> ===Total demand for new capacity===<br /> The electricity capacity required to meet the demand per region is based on a forecast of the maximum electricity demand plus a reserve margin of about 10% (including the capacity credit assigned to different forms of electricity generation). Maximum demand is calculated on the basis of an assumed monthly shape of the load duration curve (LDC) and the gross electricity demand. The latter comprises the net electricity demand from the end-use sectors plus electricity trade and transmission losses ({{AbbrTemplate|LDC}} accounts for characteristics such as cooling and lighting demand). The demand for new generation capacity is the difference between the required and existing capacity. Power plants are assumed to be replaced at the end of their lifetime, which varies from 30 to 50 years, depending on the technology and is currently fixed in the model.<br /> <br /> ===Decisions to invest in specific options ===<br /> In the following step, a decision is made to invest in different generation technologies. In the model, this is done on the basis of the price of electricity (in {{AbbrTemplate|USD/kWhe}} produced per technology, using a multinomial logit equation that assigns larger market shares to the lower cost options. The specific costs of each option is broken down into a number of categories: investment or capital costs (USD/kWe), fuel costs ([[HasAcronym::USD/GJ]]), operational and maintenance costs (OM) and other costs (see further). An exception is hydropower capacity, which is exogenously prescribed, because large hydropower plants often have functions other than only electricity production (e.g. water supply and flood control). In the equations, some constraints are added to account for limitations in supply (e.g. restrictions on biomass availability). The investments needed for each option are given in the form of total investment in new generation capacity and the share of each individual technology (determined on the basis of price and preference).<br /> <br /> ===Operational strategy===<br /> Use of power plants is based on operational costs, with low-cost technologies assumed to be used most often. This implies that capital-intensive plants with low operational costs, such as renewable and nuclear energy, operate as many hours as possible. To some degree, this is also true for other plants with low operational costs, such as coal. <br /> The operational decision is presented in the following three steps:<br /> #Renewable sources PV and wind are assigned, followed by hydropower, because these options have the lowest operational costs;<br /> #The peak load capacity (period of high electricity demand) is assigned on the basis of the operational costs of each available plant and the ability of these plants to provide peak load capacity; <br /> #Base load (period of medium to low energy demand) is assigned on the basis of the remaining capacity (after steps 1 and 2), operational costs and the ability of options to provide the base load capacity.<br /> <br /> <br /> ===Fossil-fuel and bio-energy power plants===<br /> A total of 20 types of power plants generating electricity using fossil fuels and bioenergy are included. These power plants represent different combinations of conventional technology, such as gasification and combined cycle (CC) technology; combined heat and power (CHP); and carbon capture and storage (CCS;(Hendriks et al., 2004b). The specific capital costs and thermal efficiencies of these types of plants are determined by exogenous assumptions that describe the technological progress of typical components of these plants:<br /> *For conventional power plants, the coal-fired plant is defined in terms of overall efficiency and investment cost. The characteristics of all other conventional plants (using oil, natural gas or bioenergy) are described in the investment differences for desulphurisation, fuel handling and efficiency.<br /> *For Combined Cycle (CC) power plants, the characteristics of a natural gas fired plant are set as the standard. Other CC plants (fuelled by oil, bioenergy and coal after gasification) are defined by indicating additional capital costs for gasification, efficiency losses due to gasification, and operation and maintenance (O&amp;M) costs for fuel handling. <br /> *Power plants with carbon-capture-and-storage systems (CCS) are assumed to be CC plants, but with fuel-specific lower efficiency and higher investment and O&amp;M costs (related to capture and storage). <br /> *The characteristics of combined-heat-and-power plants (CHP) are similar to those of other plants, but with an assumed small increase in capital costs, in combination with a lower efficiency for electric conversion and an added factor for heat efficiency. <br /> <br /> The cost of one unit electricity generated is equal to the sum of the capital cost, operational and maintenance costs (O&amp;M), fuel cost, and CO2 storage cost.<br /> <br /> ===Solar and wind power===<br /> <br /> The costs of solar and wind power in the model are determined by learning and depletion dynamics. For renewable energy, costs relate to capital, O&amp;M and system integration. The capital costs mostly relate to learning and depletion processes. Learning is represented by in learning curves (Box 4.1.3.1); depletion is by long-term in cost–supply curves. <br /> <br /> The additional system integration costs relate to curtailed electricity (if production exceeds demand and the overcapacity cannot be used within the system), backup capacity; and additional required spinning reserve. The last items are needed to avoid loss of power if the supply of wind or solar power drops suddenly, enabling a power scale up in a relatively short time, in power stations operating below maximum capacity ([[Hoogwijk, 2004]]).<br /> <br /> To determine curtailed electricity, the model compares 10 points on the load-demand curve at the overlap between demand and supply. For both wind and solar power, a typical load supply curve is assumed (see [[Hoogwijk, 2004]]). If supply exceeds demand, the overcapacity in electricity is assumed to be discarded, resulting in higher production costs.<br /> <br /> Because wind and solar power supply is intermittent (variable and thus not reliable), the model assumes that backup capacity needs to be installed. It is assumed that no backup is required for first 5% penetration of the intermittent capacity. However, for higher levels of penetration, the effective capacity (degree to which operators can rely on plants producing at a specific time) of intermittent resources is assumed to decrease. This is referred to as the capacity factor. This decrease leads to the need for backup power by low-cost options, such as gas turbines, the cost of which is allocated to the intermittent source.<br /> <br /> The required spinning reserve of the power system is the capacity that can be used to respond to a rapid increase in demand. This is assumed to be 3.5% of the installed capacity of a conventional power plant. If wind and solar power further penetrate the market, the model assumes an additional, required spinning reserve of 15% of the intermittent capacity (after subtraction of the 3.5% existing capacity). The related costs are allocated to the intermittent source.<br /> <br /> <br /> {{FormulaAndTableTemplate|Formula1_ED}}<br /> <br /> The costs of solar and wind power are the model determined by learning and depletion dynamics. For renewable energy, costs relate to capital, O&amp;M and system integration. The capital costs mostly relate to [[Energy conversion/Description/Technical learning|learning]] and depletion processes (learning is represented by so-called learning curves; depletion is represented by long-term cost–supply curves). <br /> <br /> The additional system integration costs relate to <br /> # Discarded electricity in cases where production exceeds demand and the overcapacity cannot be used within the system;<br /> # Back-up capacity;<br /> # Additional required spinning reserve;<br /> The two last items are needed to avoid loss of power if the supply of wind or solar power suddenly drops, enabling a power scale up in a relatively short time, in power stations operating below maximum capacity ([[Hoogwijk, 2004]]).<br /> *To determine discarded electricity, the model makes a comparison between 10 different points on the load-demand curve, at the overlap between demand and supply. For both wind and solar power, a typical load–supply curve is assumed (see [[Hoogwijk, 2004]]). If supply exceeds demand, the overcapacity in electricity is assumed to be discarded, resulting in higher production costs. <br /> *Because wind and solar power supply is intermittent (i.e. it varies and therefore is not reliable), the model assumes that so-called back-up capacity needs to be installed. For the first 5% penetration of the intermittent capacity, it is assumed that no-back is required. However, for higher levels of penetration, the effective capacity (i.e. degree to which operators can rely on plants producing at a particular moment in time) of intermittent resources is assumed to decrease (referred to as the capacity factor). This decrease leads to the need of back-up power(by low-cost options, such as gas turbines), the costs of which are allocated to the intermittent source.<br /> *The required spinning reserve of the power system (capacity that can be used to respond to a rapid increase in demand) is assumed to be 3.5% of the installed capacity of a conventional power plant. If wind and solar power further penetrate the market, the model assumes an additional, required spinning reserve of 15% of the intermittent capacity (but after first subtracting the 3.5% existing capacity). The related costs are allocated to the intermittent source.<br /> <br /> ==Nuclear power==<br /> For nuclear power, the costs also consists of capital, O&amp;M and nuclear fuel costs. Similar to the renewable energy options, technology improvement nuclear power is described via a learning curve (so costs decrease with cumulative installed capacity). At the same time, fuel costs increase as a function of depletion. Fuel costs are determined on the basis of the estimated extraction costs of uranium and thorium resources, as is described in the component [[Energy supply]]. A small trade model for these fission fuels is included.<br /> <br /> ==Hydrogen generation model==<br /> The structure of the hydrogen model is similar to that of the electric power model ([[Van Ruijven et al., 2007]]). There are, however, some important differences:<br /> *The hydrogen model distinguishes the following 11 supply options: hydrogen production plants on the basis of coal, oil, natural gas and bio-energy, with and <br /> without carbon capture and storage (8 plants), hydrogen production from electrolysis, direct hydrogen production from solar thermal processes, and, finally, small methane reform plants. <br /> *For simplification, no description of preferences for different power plants is accounted for in the operational strategy. In other words, the load factor for each option equals the total production divided by the capacity for each region.<br /> *Intermittence does not play an important role, as hydrogen can be stored to some degree. Therefore, there are no equations simulating system integration.<br /> *Hydrogen can be traded. Therefore, a trade model is added, similar to the trade models for fossil fuels, as is described in the [[Energy supply]] section.<br /> <br /> &lt;references/&gt;<br /> }}</div>

JoeriOostenrijk https://models.pbl.nl/index.php?title=Energy_conversion&diff=21497 2014-05-08T15:31:33Z

<p>JoeriOostenrijk: </p> <hr /> <div>{{ComponentTemplate2<br /> |Application=ADVANCE-WP5 project;<br /> |IMAGEComponent=Energy supply and demand; Energy demand; Energy supply; Agricultural systems; Climate policy; Scenario drivers;<br /> |KeyReference=Hoogwijk et al., 2007; Hendriks et al., 2004a;<br /> |InputVar=Energy policy; Air pollution policy; Demand for electricity, heat and hydrogen; Primary energy price; Carbon storage price; Carbon price; Technology development of energy conversion;<br /> |Parameter=Initial technology cost; Rules on use of technology;<br /> |OutputVar=Electricity price; Demand for primary energy; CO2 stored; Energy and industry activity level;<br /> |Description=Energy from primary sources often has to be converted into secondary energy carriers that are more easily accessible for final consumption, for example the production of electricity and hydrogen, oil products from crude oil in refineries, and fuels from biomass. Studies on transitions to more sustainable energy systems also show the importance of these conversions for the future.<br /> <br /> The energy conversion module of TIMER simulates the choices of input energy carriers in two steps. In the first step, investment decisions are made on the future generation mix in terms of newly added capital. In the second step, the actual use of the capacity in place depends on a set of model rules that determine the purpose and how frequently the different types of power plants are used (baseload/peakload). The discussion focuses on the production of electricity and hydrogen. Other conversion processes have only be implemented in the model by simple multipliers, as they mostly convert energy from a single primary source to one secondary energy carrier. These processes are discussed in [[Energy supply]].<br /> |ComponentCode=EC<br /> |AggregatedComponent=Energy supply and demand<br /> |FrameworkElementType=pressure component<br /> }}</div>

JoeriOostenrijk https://models.pbl.nl/index.php?title=Energy_conversion&diff=21496 2014-05-08T15:31:14Z

<p>JoeriOostenrijk: </p> <hr /> <div>{{ComponentTemplate2<br /> |Application=ADVANCE-WP5 project;<br /> |IMAGEComponent=Energy supply and demand; Energy demand; Energy supply; Agricultural systems; Climate policy; Scenario drivers;<br /> |KeyReference=Hoogwijk et al., 2007; Hendriks et al., 2004a;<br /> |InputVar=Energy policy; Air pollution policy; Demand for electricity, heat and hydrogen; Primary energy price; Carbon storage price; Carbon price; Technology development of energy conversion;<br /> |Parameter=Initial technology cost; Rules on use of technology;<br /> |OutputVar=Electricity price; Demand for primary energy; CO2 stored; Energy and industry activity level;<br /> |Description=Energy from primary sources often has to be converted into secondary energy carriers that are more easily accessible for final consumption, for example the production of electricity and hydrogen, oil products from crude oil in refineries, and fuels from biomass. Studies on transitions to more sustainable energy systems also show the importance of these conversions for the future.<br /> <br /> The energy conversion module of TIMER simulates the choices of input energy carriers in two steps. In the first step, investment decisions are made on the future generation mix in terms of newly added capital. In the second step, the actual use of the capacity in place depends on a set of model rules that determine the purpose and how frequently the different types of power plants are used (baseload/peakload). The discussion focuses on the production of electricity and hydrogen. Other conversion processes have only be implemented in the model by simple multipliers, as they mostly convert energy from a single primary source to one secondary energy carrier. These processes are discussed in [[Energy supply|Energy Supply.]].<br /> |ComponentCode=EC<br /> |AggregatedComponent=Energy supply and demand<br /> |FrameworkElementType=pressure component<br /> }}</div>

JoeriOostenrijk https://models.pbl.nl/index.php?title=Energy_conversion&diff=21495 2014-05-08T15:30:30Z

<p>JoeriOostenrijk: </p> <hr /> <div>{{ComponentTemplate2<br /> |Application=ADVANCE-WP5 project;<br /> |IMAGEComponent=Energy supply and demand; Energy demand; Energy supply; Agricultural systems; Climate policy; Scenario drivers;<br /> |KeyReference=Hoogwijk et al., 2007; Hendriks et al., 2004a;<br /> |InputVar=Energy policy; Air pollution policy; Demand for electricity, heat and hydrogen; Primary energy price; Carbon storage price; Carbon price; Technology development of energy conversion;<br /> |Parameter=Initial technology cost; Rules on use of technology;<br /> |OutputVar=Electricity price; Demand for primary energy; CO2 stored; Energy and industry activity level;<br /> |Description=Energy from primary sources often has to be converted into secondary energy carriers that are more easily accessible for final consumption, for example the production of electricity and hydrogen, oil products from crude oil in refineries, and fuels from biomass. Studies on transitions to more sustainable energy systems also show the importance of these conversions for the future.<br /> <br /> The energy conversion module of TIMER simulates the choices of input energy carriers in two steps. In the first step, investment decisions are made on the future generation mix in terms of newly added capital. In the second step, the actual use of the capacity in place depends on a set of model rules that determine the purpose and how frequently the different types of power plants are used (baseload/peakload). The discussion focuses on the production of electricity and hydrogen. Other conversion processes have only be implemented in the model by simple multipliers, as they mostly convert energy from a single primary source to one secondary energy carrier. These processes are discussed in [[Energy supply|primary energy (sub)model]].<br /> |ComponentCode=EC<br /> |AggregatedComponent=Energy supply and demand<br /> |FrameworkElementType=pressure component<br /> }}</div>

JoeriOostenrijk https://models.pbl.nl/index.php?title=Energy_conversion&diff=21494 2014-05-08T15:29:04Z

<p>JoeriOostenrijk: </p> <hr /> <div>{{ComponentTemplate2<br /> |Application=ADVANCE-WP5 project;<br /> |IMAGEComponent=Energy supply and demand; Energy demand; Energy supply; Agricultural systems; Climate policy; Scenario drivers;<br /> |KeyReference=Hoogwijk et al., 2007; Hendriks et al., 2004a;<br /> |InputVar=Energy policy; Air pollution policy; Demand for electricity, heat and hydrogen; Primary energy price; Carbon storage price; Carbon price; Technology development of energy conversion; <br /> |OutputVar=Electricity price; Demand for primary energy; CO2 stored; Energy and industry activity level;<br /> |Parameter=Initial technology cost; Rules on use of technology;<br /> |Description=Energy from primary sources often is first converted into secondary energy carriers that are more easily accessible for final consumption. Examples of such conversion processes relate to the production of electricity and hydrogen, oil products from crude oil in refineries, and the production of fuels from biomass. Electricity (and in the future possibly also hydrogen) is produced by the conversion of primary energy carriers, such as fossil fuels, fissile materials (uranium), and various renewable energy sources. Studies on transitions towards more sustainable energy systems tend to show the importance of these conversions for the future. <br /> <br /> In two steps, the conversion models in the IMAGE Energy model simulate the choices made between input energy carriers. In the first step, at the level of newly added capital, investment decisions are made on the future generation mix. In the second step, the actual operationuse of the capacity in place depends on a set of model rules that determine how often the different types of power plants are used. and for what purpose (baseload/peakload). The discussion here concentrates on the production of electricity and hydrogen. Other conversion processes are relatively simple, as they mostly convert energy from a single primary source to one secondary energy carrier; these are therefore discussed in the [[Energy supply|primary energy (sub)model]].<br /> |ComponentCode=EC<br /> |AggregatedComponent=Energy supply and demand<br /> |FrameworkElementType=pressure component<br /> }}</div>

JoeriOostenrijk https://models.pbl.nl/index.php?title=Energy_conversion/Description&diff=21493 2014-05-08T15:26:32Z

<p>JoeriOostenrijk: </p> <hr /> <div>{{ComponentDescriptionTemplate<br /> |Reference=Hoogwijk, 2004; Van Vuuren, 2007; Hendriks et al., 2004b; Van Ruijven et al., 2007;<br /> |Description=[[TIMER model|TIMER]] includes two main energy conversion modules: Electric power generation and hydrogen generation. Below, electric power generation is described in detail. In addition, the key characteristics of the hydrogen generation model, which follows a similar structure, are presented.<br /> <br /> ==Electric power generation==<br /> As shown in the flowchart, two key elements of the electric power generation are the investment strategy and the operational strategy in the sector. A challenge in simulating electricity production in an aggregated model is that in reality electricity production depends on a range of complex factors, related to costs, reliance, and the time required to switch on technologies. Modelling these factors requires a high level of detail and thus {{AbbrTemplate|IAM}}s such as [[TIMER model|TIMER]] concentrate on introducing a set of simplified, meta relationships ([[Hoogwijk, 2004]]; [[Van Vuuren, 2007]]).<br /> <br /> ===Total demand for new capacity===<br /> The electricity capacity required to meet the demand per region is based on a forecast of the maximum electricity demand plus a reserve margin of about 10% (including the capacity credit assigned to different forms of electricity generation). Maximum demand is calculated on the basis of an assumed monthly shape of the load duration curve (LDC) and the gross electricity demand. The latter comprises the net electricity demand from the end-use sectors plus electricity trade and transmission losses ({{AbbrTemplate|LDC}} accounts for characteristics such as cooling and lighting demand). The demand for new generation capacity is the difference between the required and existing capacity. Power plants are assumed to be replaced at the end of their lifetime, which varies from 30 to 50 years, depending on the technology and is currently fixed in the model.<br /> <br /> ===Decisions to invest in specific options ===<br /> In the following step, a decision is made to invest in different generation technologies. In the model, this is done on the basis of the price of electricity (in {{AbbrTemplate|USD/kWhe}} produced per technology, using a multinomial logit equation that assigns larger market shares to the lower cost options. The specific costs of each option is broken down into a number of categories: investment or capital costs (USD/kWe), fuel costs ([[HasAcronym::USD/GJ]]), operational and maintenance costs (OM) and other costs (see further). An exception is hydropower capacity, which is exogenously prescribed, because large hydropower plants often have functions other than only electricity production (e.g. water supply and flood control). In the equations, some constraints are added to account for limitations in supply (e.g. restrictions on biomass availability). The investments needed for each option are given in the form of total investment in new generation capacity and the share of each individual technology (determined on the basis of price and preference).<br /> <br /> ==Operational strategy ==<br /> For the operational strategy, the use of power plants is based on operational costs: low-cost technologies are assumed to be used most often. This implies that capital-intensive plants with low operational costs, such as those for renewable and nuclear energy, in principle, will operate as many hours as possible. To some degree, this is also true for other plants with low operational costs (e.g. coal). Therefore, the operational decision is represented by the following three steps:<br /> #First, the renewable sources PV and wind are assigned, followed by hydropower, as these options have the lowest operational costs;<br /> #Second, the peak load capacity (i.e. period of high electricity demand) is assigned on the basis of operational costs of each available plant and the ability of these plants to provide such peak load capacity; <br /> #Third, base load (i.e. period of medium to low energy demand) is assigned on the basis of the remaining capacity (after steps 1 and 2), operational costs and the ability of options to provide the base load capacity.<br /> <br /> ==Fossil-fuel and bio-energy power plants==<br /> A total of 20 different types of power plants, generating electricity using fossil fuels and bio-energy, are included. These power plants represent different combinations of (i) conventional technology; (ii) gasification and combined cycle ([[HasAcronym::CC]]) technology; (iii) combined heat and power ([[HasAcronym::CHP]]) and, (iv) carbon capture and storage ([[HasAcronym::CCS]]) ([[Hendriks et al., 2004b]]). The specific capital costs and thermal efficiencies of these types of plants are determined by exogenous assumptions that describe the technological progress of typical components of these plants:<br /> *For conventional power plants, the coal-fired plant is defined in terms of overall efficiency and investment costs. The characteristics of all other conventional plants (using oil, natural gas or bio-energy) here are described in the investment differences for desulphurisation, fuel handling and efficiency.<br /> *For Combined Cycle (CC) power plants, the characteristics of a natural gas fuelled plant is set asthe standard. Other such plants (fuelled by oil, bio-energy and coal) are defined by indicating additional capital costs for gasification, efficiency losses due to gasification, and operation and maintenance ([[HasAcronym::O &amp; M]]) costs for fuel handling. <br /> *Power plants with carbon-capture-and-storage systems (CCS) are assumed to be CC plants, but with fuel-specific lower efficiency and higher investment and O&amp;M costs (related to capture and storage). <br /> *The characteristics of combined-heat-and-power plants (CHP) are similar to those of other plants, but with an assumed small increase in capital costs, in combination with a lower efficiency for electric conversion and an added factor for heat efficiency. <br /> <br /> The costs of one unit of electricity generated in these plants is equal to the sum of the capital costs, operation and maintenance costs (O&amp;M), fuel costs, and CO2 storage costs. <br /> <br /> ==Solar and wind power==<br /> <br /> {{FormulaAndTableTemplate|Formula1_ED}}<br /> <br /> The costs of solar and wind power are the model determined by learning and depletion dynamics. For renewable energy, costs relate to capital, O&amp;M and system integration. The capital costs mostly relate to [[Energy conversion/Description/Technical learning|learning]] and depletion processes (learning is represented by so-called learning curves; depletion is represented by long-term cost–supply curves). <br /> <br /> The additional system integration costs relate to <br /> # Discarded electricity in cases where production exceeds demand and the overcapacity cannot be used within the system;<br /> # Back-up capacity;<br /> # Additional required spinning reserve;<br /> The two last items are needed to avoid loss of power if the supply of wind or solar power suddenly drops, enabling a power scale up in a relatively short time, in power stations operating below maximum capacity ([[Hoogwijk, 2004]]).<br /> *To determine discarded electricity, the model makes a comparison between 10 different points on the load-demand curve, at the overlap between demand and supply. For both wind and solar power, a typical load–supply curve is assumed (see [[Hoogwijk, 2004]]). If supply exceeds demand, the overcapacity in electricity is assumed to be discarded, resulting in higher production costs. <br /> *Because wind and solar power supply is intermittent (i.e. it varies and therefore is not reliable), the model assumes that so-called back-up capacity needs to be installed. For the first 5% penetration of the intermittent capacity, it is assumed that no-back is required. However, for higher levels of penetration, the effective capacity (i.e. degree to which operators can rely on plants producing at a particular moment in time) of intermittent resources is assumed to decrease (referred to as the capacity factor). This decrease leads to the need of back-up power(by low-cost options, such as gas turbines), the costs of which are allocated to the intermittent source.<br /> *The required spinning reserve of the power system (capacity that can be used to respond to a rapid increase in demand) is assumed to be 3.5% of the installed capacity of a conventional power plant. If wind and solar power further penetrate the market, the model assumes an additional, required spinning reserve of 15% of the intermittent capacity (but after first subtracting the 3.5% existing capacity). The related costs are allocated to the intermittent source.<br /> <br /> ==Nuclear power==<br /> For nuclear power, the costs also consists of capital, O&amp;M and nuclear fuel costs. Similar to the renewable energy options, technology improvement nuclear power is described via a learning curve (so costs decrease with cumulative installed capacity). At the same time, fuel costs increase as a function of depletion. Fuel costs are determined on the basis of the estimated extraction costs of uranium and thorium resources, as is described in the component [[Energy supply]]. A small trade model for these fission fuels is included.<br /> <br /> ==Hydrogen generation model==<br /> The structure of the hydrogen model is similar to that of the electric power model ([[Van Ruijven et al., 2007]]). There are, however, some important differences:<br /> *The hydrogen model distinguishes the following 11 supply options: hydrogen production plants on the basis of coal, oil, natural gas and bio-energy, with and <br /> without carbon capture and storage (8 plants), hydrogen production from electrolysis, direct hydrogen production from solar thermal processes, and, finally, small methane reform plants. <br /> *For simplification, no description of preferences for different power plants is accounted for in the operational strategy. In other words, the load factor for each option equals the total production divided by the capacity for each region.<br /> *Intermittence does not play an important role, as hydrogen can be stored to some degree. Therefore, there are no equations simulating system integration.<br /> *Hydrogen can be traded. Therefore, a trade model is added, similar to the trade models for fossil fuels, as is described in the [[Energy supply]] section.<br /> <br /> &lt;references/&gt;<br /> }}</div>

JoeriOostenrijk https://models.pbl.nl/index.php?title=Energy_conversion/Description&diff=21492 2014-05-08T15:24:33Z

<p>JoeriOostenrijk: </p> <hr /> <div>{{ComponentDescriptionTemplate<br /> |Reference=Hoogwijk, 2004; Van Vuuren, 2007; Hendriks et al., 2004b; Van Ruijven et al., 2007;<br /> |Description=[[TIMER model|TIMER]] includes two main energy conversion modules: Electric power generation and hydrogen generation. Below, electric power generation is described in detail. In addition, the key characteristics of the hydrogen generation model, which follows a similar structure, are presented.<br /> <br /> ==Electric power generation==<br /> As shown in the flowchart, two key elements of the electric power generation are the investment strategy and the operational strategy in the sector. A challenge in simulating electricity production in an aggregated model is that in reality electricity production depends on a range of complex factors, related to costs, reliance, and the time required to switch on technologies. Modelling these factors requires a high level of detail and thus {{AbbrTemplate|IAM}}s such as [[TIMER model|TIMER]] concentrate on introducing a set of simplified, meta relationships ([[Hoogwijk, 2004]]; [[Van Vuuren, 2007]]). <br /> <br /> <br /> As shown in the flowdiagram, two key elements of the electric power generation model are the descriptions of the investment strategy and the operational strategy within the sector. A challenge of simulating electricity production in an aggregated model is that, in reality, electricity production depends on a whole range of complex factors, such as those related to costs, reliance, and the time it takes to switch on technologies. Modelling these factors requires a very high level of detail. Therefore, IAMs such as TIMER concentrate on introducing a set of simplified, meta relationships ([[Hoogwijk, 2004]]; [[Van Vuuren, 2007]]). <br /> <br /> ===Total demand for new capacity===<br /> <br /> The electricity capacity required to meet the demand per region is based on a forecast of the maximum electricity demand plus a reserve margin of about 10% (including the capacity credit assigned to different forms of electricity generation). Maximum demand is calculated on the basis of an assumed monthly shape of the load duration curve (LDC) and the gross electricity demand. The latter comprises the net electricity demand from the end-use sectors plus electricity trade and transmission losses (LDC accounts for characteristics such as cooling and lighting demand). The demand for new generation capacity is the difference between the required and existing capacity. Power plants are assumed to be replaced at the end of their lifetime, which varies from 30 to 50 years, depending on the technology and is currently fixed in the model.<br /> The required electricity capacity needed to meet the demand per region is based on a forecast of the maximum electricity demand plus a reserve margin of about 10%. The maximum demand is calculated on the basis of an assumed monthly shape of the load duration curve ([[HasAcronym::LDC]]) and the gross electricity demand. The latter comprises the net electricity demand (from the end-use sectors) plus electricity trade and transmission losses (the LDC accounts for characteristics such as cooling and lighting demand). The demand for new generation capacity equals the difference between the required and existing capacity. Here, power plants are assumed to be replaced at the end of their lifetime (depending on the technology, varying from 30 to 50 years, and currently fixed in the model).<br /> <br /> ==Decisions to invest in specific options ==<br /> In the following step, a decision is made to invest in different generation technologies. In the model, this is done on the basis of the price of electricity (in [[HasAcronym::USD/kWhe]]) produced per technology, using a multinomial logit equation that assigns larger market shares to the lower cost options. The specific costs of each option is broken down into a number of categories: investment or capital costs (USD/kWe), fuel costs ([[HasAcronym::USD/GJ]]), operational and maintenance costs (OM) and other costs (see further). An exception is hydropower capacity, which is exogenously prescribed, because large hydropower plants often have functions other than only electricity production (e.g. water supply and flood control). In the equations, some constraints are added to account for limitations in supply (e.g. restrictions on biomass availability). The investments needed for each option are given in the form of total investment in new generation capacity and the share of each individual technology (determined on the basis of price and preference).<br /> <br /> ==Operational strategy ==<br /> For the operational strategy, the use of power plants is based on operational costs: low-cost technologies are assumed to be used most often. This implies that capital-intensive plants with low operational costs, such as those for renewable and nuclear energy, in principle, will operate as many hours as possible. To some degree, this is also true for other plants with low operational costs (e.g. coal). Therefore, the operational decision is represented by the following three steps:<br /> #First, the renewable sources PV and wind are assigned, followed by hydropower, as these options have the lowest operational costs;<br /> #Second, the peak load capacity (i.e. period of high electricity demand) is assigned on the basis of operational costs of each available plant and the ability of these plants to provide such peak load capacity; <br /> #Third, base load (i.e. period of medium to low energy demand) is assigned on the basis of the remaining capacity (after steps 1 and 2), operational costs and the ability of options to provide the base load capacity.<br /> <br /> ==Fossil-fuel and bio-energy power plants==<br /> A total of 20 different types of power plants, generating electricity using fossil fuels and bio-energy, are included. These power plants represent different combinations of (i) conventional technology; (ii) gasification and combined cycle ([[HasAcronym::CC]]) technology; (iii) combined heat and power ([[HasAcronym::CHP]]) and, (iv) carbon capture and storage ([[HasAcronym::CCS]]) ([[Hendriks et al., 2004b]]). The specific capital costs and thermal efficiencies of these types of plants are determined by exogenous assumptions that describe the technological progress of typical components of these plants:<br /> *For conventional power plants, the coal-fired plant is defined in terms of overall efficiency and investment costs. The characteristics of all other conventional plants (using oil, natural gas or bio-energy) here are described in the investment differences for desulphurisation, fuel handling and efficiency.<br /> *For Combined Cycle (CC) power plants, the characteristics of a natural gas fuelled plant is set asthe standard. Other such plants (fuelled by oil, bio-energy and coal) are defined by indicating additional capital costs for gasification, efficiency losses due to gasification, and operation and maintenance ([[HasAcronym::O &amp; M]]) costs for fuel handling. <br /> *Power plants with carbon-capture-and-storage systems (CCS) are assumed to be CC plants, but with fuel-specific lower efficiency and higher investment and O&amp;M costs (related to capture and storage). <br /> *The characteristics of combined-heat-and-power plants (CHP) are similar to those of other plants, but with an assumed small increase in capital costs, in combination with a lower efficiency for electric conversion and an added factor for heat efficiency. <br /> <br /> The costs of one unit of electricity generated in these plants is equal to the sum of the capital costs, operation and maintenance costs (O&amp;M), fuel costs, and CO2 storage costs. <br /> <br /> ==Solar and wind power==<br /> <br /> {{FormulaAndTableTemplate|Formula1_ED}}<br /> <br /> The costs of solar and wind power are the model determined by learning and depletion dynamics. For renewable energy, costs relate to capital, O&amp;M and system integration. The capital costs mostly relate to [[Energy conversion/Description/Technical learning|learning]] and depletion processes (learning is represented by so-called learning curves; depletion is represented by long-term cost–supply curves). <br /> <br /> The additional system integration costs relate to <br /> # Discarded electricity in cases where production exceeds demand and the overcapacity cannot be used within the system;<br /> # Back-up capacity;<br /> # Additional required spinning reserve;<br /> The two last items are needed to avoid loss of power if the supply of wind or solar power suddenly drops, enabling a power scale up in a relatively short time, in power stations operating below maximum capacity ([[Hoogwijk, 2004]]).<br /> *To determine discarded electricity, the model makes a comparison between 10 different points on the load-demand curve, at the overlap between demand and supply. For both wind and solar power, a typical load–supply curve is assumed (see [[Hoogwijk, 2004]]). If supply exceeds demand, the overcapacity in electricity is assumed to be discarded, resulting in higher production costs. <br /> *Because wind and solar power supply is intermittent (i.e. it varies and therefore is not reliable), the model assumes that so-called back-up capacity needs to be installed. For the first 5% penetration of the intermittent capacity, it is assumed that no-back is required. However, for higher levels of penetration, the effective capacity (i.e. degree to which operators can rely on plants producing at a particular moment in time) of intermittent resources is assumed to decrease (referred to as the capacity factor). This decrease leads to the need of back-up power(by low-cost options, such as gas turbines), the costs of which are allocated to the intermittent source.<br /> *The required spinning reserve of the power system (capacity that can be used to respond to a rapid increase in demand) is assumed to be 3.5% of the installed capacity of a conventional power plant. If wind and solar power further penetrate the market, the model assumes an additional, required spinning reserve of 15% of the intermittent capacity (but after first subtracting the 3.5% existing capacity). The related costs are allocated to the intermittent source.<br /> <br /> ==Nuclear power==<br /> For nuclear power, the costs also consists of capital, O&amp;M and nuclear fuel costs. Similar to the renewable energy options, technology improvement nuclear power is described via a learning curve (so costs decrease with cumulative installed capacity). At the same time, fuel costs increase as a function of depletion. Fuel costs are determined on the basis of the estimated extraction costs of uranium and thorium resources, as is described in the component [[Energy supply]]. A small trade model for these fission fuels is included.<br /> <br /> ==Hydrogen generation model==<br /> The structure of the hydrogen model is similar to that of the electric power model ([[Van Ruijven et al., 2007]]). There are, however, some important differences:<br /> *The hydrogen model distinguishes the following 11 supply options: hydrogen production plants on the basis of coal, oil, natural gas and bio-energy, with and <br /> without carbon capture and storage (8 plants), hydrogen production from electrolysis, direct hydrogen production from solar thermal processes, and, finally, small methane reform plants. <br /> *For simplification, no description of preferences for different power plants is accounted for in the operational strategy. In other words, the load factor for each option equals the total production divided by the capacity for each region.<br /> *Intermittence does not play an important role, as hydrogen can be stored to some degree. Therefore, there are no equations simulating system integration.<br /> *Hydrogen can be traded. Therefore, a trade model is added, similar to the trade models for fossil fuels, as is described in the [[Energy supply]] section.<br /> <br /> &lt;references/&gt;<br /> }}</div>

JoeriOostenrijk https://models.pbl.nl/index.php?title=Energy_conversion/Description&diff=21491 2014-05-08T15:21:27Z

<p>JoeriOostenrijk: </p> <hr /> <div>{{ComponentDescriptionTemplate<br /> |Reference=Hoogwijk, 2004; Van Vuuren, 2007; Hendriks et al., 2004b; Van Ruijven et al., 2007;<br /> |Description=The [[TIMER model]] includes two energy conversion submodels: the electric power generation model and the hydrogen generation model. Here, the focus is on a description of the electric power generation model (The flowdiagram on the right also shows only the electricity model). The hydrogen model follows a similar structure, and its key characteristics are briefly discussed in this Section. <br /> <br /> Electric power generation<br /> As shown in the flowdiagram, two key elements of the electric power generation model are the descriptions of the investment strategy and the operational strategy within the sector. A challenge of simulating electricity production in an aggregated model is that, in reality, electricity production depends on a whole range of complex factors, such as those related to costs, reliance, and the time it takes to switch on technologies. Modelling these factors requires a very high level of detail. Therefore, IAMs such as TIMER concentrate on introducing a set of simplified, meta relationships ([[Hoogwijk, 2004]]; [[Van Vuuren, 2007]]). <br /> <br /> ==Total demand for new capacity en nu een helee lange koptekst die er af loop==<br /> The required electricity capacity needed to meet the demand per region is based on a forecast of the maximum electricity demand plus a reserve margin of about 10%. The maximum demand is calculated on the basis of an assumed monthly shape of the load duration curve ([[HasAcronym::LDC]]) and the gross electricity demand. The latter comprises the net electricity demand (from the end-use sectors) plus electricity trade and transmission losses (the LDC accounts for characteristics such as cooling and lighting demand). The demand for new generation capacity equals the difference between the required and existing capacity. Here, power plants are assumed to be replaced at the end of their lifetime (depending on the technology, varying from 30 to 50 years, and currently fixed in the model).<br /> <br /> ==Decisions to invest in specific options ==<br /> In the following step, a decision is made to invest in different generation technologies. In the model, this is done on the basis of the price of electricity (in [[HasAcronym::USD/kWhe]]) produced per technology, using a multinomial logit equation that assigns larger market shares to the lower cost options. The specific costs of each option is broken down into a number of categories: investment or capital costs (USD/kWe), fuel costs ([[HasAcronym::USD/GJ]]), operational and maintenance costs (OM) and other costs (see further). An exception is hydropower capacity, which is exogenously prescribed, because large hydropower plants often have functions other than only electricity production (e.g. water supply and flood control). In the equations, some constraints are added to account for limitations in supply (e.g. restrictions on biomass availability). The investments needed for each option are given in the form of total investment in new generation capacity and the share of each individual technology (determined on the basis of price and preference).<br /> <br /> ==Operational strategy ==<br /> For the operational strategy, the use of power plants is based on operational costs: low-cost technologies are assumed to be used most often. This implies that capital-intensive plants with low operational costs, such as those for renewable and nuclear energy, in principle, will operate as many hours as possible. To some degree, this is also true for other plants with low operational costs (e.g. coal). Therefore, the operational decision is represented by the following three steps:<br /> #First, the renewable sources PV and wind are assigned, followed by hydropower, as these options have the lowest operational costs;<br /> #Second, the peak load capacity (i.e. period of high electricity demand) is assigned on the basis of operational costs of each available plant and the ability of these plants to provide such peak load capacity; <br /> #Third, base load (i.e. period of medium to low energy demand) is assigned on the basis of the remaining capacity (after steps 1 and 2), operational costs and the ability of options to provide the base load capacity.<br /> <br /> ==Fossil-fuel and bio-energy power plants==<br /> A total of 20 different types of power plants, generating electricity using fossil fuels and bio-energy, are included. These power plants represent different combinations of (i) conventional technology; (ii) gasification and combined cycle ([[HasAcronym::CC]]) technology; (iii) combined heat and power ([[HasAcronym::CHP]]) and, (iv) carbon capture and storage ([[HasAcronym::CCS]]) ([[Hendriks et al., 2004b]]). The specific capital costs and thermal efficiencies of these types of plants are determined by exogenous assumptions that describe the technological progress of typical components of these plants:<br /> *For conventional power plants, the coal-fired plant is defined in terms of overall efficiency and investment costs. The characteristics of all other conventional plants (using oil, natural gas or bio-energy) here are described in the investment differences for desulphurisation, fuel handling and efficiency.<br /> *For Combined Cycle (CC) power plants, the characteristics of a natural gas fuelled plant is set asthe standard. Other such plants (fuelled by oil, bio-energy and coal) are defined by indicating additional capital costs for gasification, efficiency losses due to gasification, and operation and maintenance ([[HasAcronym::O &amp; M]]) costs for fuel handling. <br /> *Power plants with carbon-capture-and-storage systems (CCS) are assumed to be CC plants, but with fuel-specific lower efficiency and higher investment and O&amp;M costs (related to capture and storage). <br /> *The characteristics of combined-heat-and-power plants (CHP) are similar to those of other plants, but with an assumed small increase in capital costs, in combination with a lower efficiency for electric conversion and an added factor for heat efficiency. <br /> <br /> The costs of one unit of electricity generated in these plants is equal to the sum of the capital costs, operation and maintenance costs (O&amp;M), fuel costs, and CO2 storage costs. <br /> <br /> ==Solar and wind power==<br /> <br /> {{FormulaAndTableTemplate|Formula1_ED}}<br /> <br /> The costs of solar and wind power are the model determined by learning and depletion dynamics. For renewable energy, costs relate to capital, O&amp;M and system integration. The capital costs mostly relate to [[Energy conversion/Description/Technical learning|learning]] and depletion processes (learning is represented by so-called learning curves; depletion is represented by long-term cost–supply curves). <br /> <br /> The additional system integration costs relate to <br /> # Discarded electricity in cases where production exceeds demand and the overcapacity cannot be used within the system;<br /> # Back-up capacity;<br /> # Additional required spinning reserve;<br /> The two last items are needed to avoid loss of power if the supply of wind or solar power suddenly drops, enabling a power scale up in a relatively short time, in power stations operating below maximum capacity ([[Hoogwijk, 2004]]).<br /> *To determine discarded electricity, the model makes a comparison between 10 different points on the load-demand curve, at the overlap between demand and supply. For both wind and solar power, a typical load–supply curve is assumed (see [[Hoogwijk, 2004]]). If supply exceeds demand, the overcapacity in electricity is assumed to be discarded, resulting in higher production costs. <br /> *Because wind and solar power supply is intermittent (i.e. it varies and therefore is not reliable), the model assumes that so-called back-up capacity needs to be installed. For the first 5% penetration of the intermittent capacity, it is assumed that no-back is required. However, for higher levels of penetration, the effective capacity (i.e. degree to which operators can rely on plants producing at a particular moment in time) of intermittent resources is assumed to decrease (referred to as the capacity factor). This decrease leads to the need of back-up power(by low-cost options, such as gas turbines), the costs of which are allocated to the intermittent source.<br /> *The required spinning reserve of the power system (capacity that can be used to respond to a rapid increase in demand) is assumed to be 3.5% of the installed capacity of a conventional power plant. If wind and solar power further penetrate the market, the model assumes an additional, required spinning reserve of 15% of the intermittent capacity (but after first subtracting the 3.5% existing capacity). The related costs are allocated to the intermittent source.<br /> <br /> ==Nuclear power==<br /> For nuclear power, the costs also consists of capital, O&amp;M and nuclear fuel costs. Similar to the renewable energy options, technology improvement nuclear power is described via a learning curve (so costs decrease with cumulative installed capacity). At the same time, fuel costs increase as a function of depletion. Fuel costs are determined on the basis of the estimated extraction costs of uranium and thorium resources, as is described in the component [[Energy supply]]. A small trade model for these fission fuels is included.<br /> <br /> ==Hydrogen generation model==<br /> The structure of the hydrogen model is similar to that of the electric power model ([[Van Ruijven et al., 2007]]). There are, however, some important differences:<br /> *The hydrogen model distinguishes the following 11 supply options: hydrogen production plants on the basis of coal, oil, natural gas and bio-energy, with and <br /> without carbon capture and storage (8 plants), hydrogen production from electrolysis, direct hydrogen production from solar thermal processes, and, finally, small methane reform plants. <br /> *For simplification, no description of preferences for different power plants is accounted for in the operational strategy. In other words, the load factor for each option equals the total production divided by the capacity for each region.<br /> *Intermittence does not play an important role, as hydrogen can be stored to some degree. Therefore, there are no equations simulating system integration.<br /> *Hydrogen can be traded. Therefore, a trade model is added, similar to the trade models for fossil fuels, as is described in the [[Energy supply]] section.<br /> <br /> &lt;references/&gt;<br /> }}</div>

JoeriOostenrijk https://models.pbl.nl/index.php?title=Energy_conversion/Description&diff=21490 2014-05-08T15:17:31Z

<p>JoeriOostenrijk: </p> <hr /> <div>{{ComponentDescriptionTemplate<br /> <br /> |Reference=Hoogwijk, 2004; Van Vuuren, 2007; Hendriks et al., 2004b; Van Ruijven et al., 2007;<br /> |Description=The [[TIMER model]] includes two energy conversion submodels: the electric power generation model and the hydrogen generation model. Here, the focus is on a description of the electric power generation model (The flowdiagram on the right also shows only the electricity model). The hydrogen model follows a similar structure, and its key characteristics are briefly discussed in this Section. <br /> <br /> Electric power generation<br /> As shown in the flowdiagram, two key elements of the electric power generation model are the descriptions of the investment strategy and the operational strategy within the sector. A challenge of simulating electricity production in an aggregated model is that, in reality, electricity production depends on a whole range of complex factors, such as those related to costs, reliance, and the time it takes to switch on technologies. Modelling these factors requires a very high level of detail. Therefore, IAMs such as TIMER concentrate on introducing a set of simplified, meta relationships ([[Hoogwijk, 2004]]; [[Van Vuuren, 2007]]). <br /> <br /> ==Total demand for new capacity en nu een helee lange koptekst die er af loop==<br /> The required electricity capacity needed to meet the demand per region is based on a forecast of the maximum electricity demand plus a reserve margin of about 10%. The maximum demand is calculated on the basis of an assumed monthly shape of the load duration curve ([[HasAcronym::LDC]]) and the gross electricity demand. The latter comprises the net electricity demand (from the end-use sectors) plus electricity trade and transmission losses (the LDC accounts for characteristics such as cooling and lighting demand). The demand for new generation capacity equals the difference between the required and existing capacity. Here, power plants are assumed to be replaced at the end of their lifetime (depending on the technology, varying from 30 to 50 years, and currently fixed in the model).<br /> <br /> ==Decisions to invest in specific options ==<br /> In the following step, a decision is made to invest in different generation technologies. In the model, this is done on the basis of the price of electricity (in [[HasAcronym::USD/kWhe]]) produced per technology, using a multinomial logit equation that assigns larger market shares to the lower cost options. The specific costs of each option is broken down into a number of categories: investment or capital costs (USD/kWe), fuel costs ([[HasAcronym::USD/GJ]]), operational and maintenance costs (OM) and other costs (see further). An exception is hydropower capacity, which is exogenously prescribed, because large hydropower plants often have functions other than only electricity production (e.g. water supply and flood control). In the equations, some constraints are added to account for limitations in supply (e.g. restrictions on biomass availability). The investments needed for each option are given in the form of total investment in new generation capacity and the share of each individual technology (determined on the basis of price and preference).<br /> <br /> ==Operational strategy ==<br /> For the operational strategy, the use of power plants is based on operational costs: low-cost technologies are assumed to be used most often. This implies that capital-intensive plants with low operational costs, such as those for renewable and nuclear energy, in principle, will operate as many hours as possible. To some degree, this is also true for other plants with low operational costs (e.g. coal). Therefore, the operational decision is represented by the following three steps:<br /> #First, the renewable sources PV and wind are assigned, followed by hydropower, as these options have the lowest operational costs;<br /> #Second, the peak load capacity (i.e. period of high electricity demand) is assigned on the basis of operational costs of each available plant and the ability of these plants to provide such peak load capacity; <br /> #Third, base load (i.e. period of medium to low energy demand) is assigned on the basis of the remaining capacity (after steps 1 and 2), operational costs and the ability of options to provide the base load capacity.<br /> <br /> ==Fossil-fuel and bio-energy power plants==<br /> A total of 20 different types of power plants, generating electricity using fossil fuels and bio-energy, are included. These power plants represent different combinations of (i) conventional technology; (ii) gasification and combined cycle ([[HasAcronym::CC]]) technology; (iii) combined heat and power ([[HasAcronym::CHP]]) and, (iv) carbon capture and storage ([[HasAcronym::CCS]]) ([[Hendriks et al., 2004b]]). The specific capital costs and thermal efficiencies of these types of plants are determined by exogenous assumptions that describe the technological progress of typical components of these plants:<br /> *For conventional power plants, the coal-fired plant is defined in terms of overall efficiency and investment costs. The characteristics of all other conventional plants (using oil, natural gas or bio-energy) here are described in the investment differences for desulphurisation, fuel handling and efficiency.<br /> *For Combined Cycle (CC) power plants, the characteristics of a natural gas fuelled plant is set asthe standard. Other such plants (fuelled by oil, bio-energy and coal) are defined by indicating additional capital costs for gasification, efficiency losses due to gasification, and operation and maintenance ([[HasAcronym::O &amp; M]]) costs for fuel handling. <br /> *Power plants with carbon-capture-and-storage systems (CCS) are assumed to be CC plants, but with fuel-specific lower efficiency and higher investment and O&amp;M costs (related to capture and storage). <br /> *The characteristics of combined-heat-and-power plants (CHP) are similar to those of other plants, but with an assumed small increase in capital costs, in combination with a lower efficiency for electric conversion and an added factor for heat efficiency. <br /> <br /> The costs of one unit of electricity generated in these plants is equal to the sum of the capital costs, operation and maintenance costs (O&amp;M), fuel costs, and CO2 storage costs. <br /> <br /> ==Solar and wind power==<br /> <br /> {{FormulaAndTableTemplate|Formula1_ED}}<br /> <br /> The costs of solar and wind power are the model determined by learning and depletion dynamics. For renewable energy, costs relate to capital, O&amp;M and system integration. The capital costs mostly relate to [[Energy conversion/Description/Technical learning|learning]] and depletion processes (learning is represented by so-called learning curves; depletion is represented by long-term cost–supply curves). <br /> <br /> The additional system integration costs relate to <br /> # Discarded electricity in cases where production exceeds demand and the overcapacity cannot be used within the system;<br /> # Back-up capacity;<br /> # Additional required spinning reserve;<br /> The two last items are needed to avoid loss of power if the supply of wind or solar power suddenly drops, enabling a power scale up in a relatively short time, in power stations operating below maximum capacity ([[Hoogwijk, 2004]]).<br /> *To determine discarded electricity, the model makes a comparison between 10 different points on the load-demand curve, at the overlap between demand and supply. For both wind and solar power, a typical load–supply curve is assumed (see [[Hoogwijk, 2004]]). If supply exceeds demand, the overcapacity in electricity is assumed to be discarded, resulting in higher production costs. <br /> *Because wind and solar power supply is intermittent (i.e. it varies and therefore is not reliable), the model assumes that so-called back-up capacity needs to be installed. For the first 5% penetration of the intermittent capacity, it is assumed that no-back is required. However, for higher levels of penetration, the effective capacity (i.e. degree to which operators can rely on plants producing at a particular moment in time) of intermittent resources is assumed to decrease (referred to as the capacity factor). This decrease leads to the need of back-up power(by low-cost options, such as gas turbines), the costs of which are allocated to the intermittent source.<br /> *The required spinning reserve of the power system (capacity that can be used to respond to a rapid increase in demand) is assumed to be 3.5% of the installed capacity of a conventional power plant. If wind and solar power further penetrate the market, the model assumes an additional, required spinning reserve of 15% of the intermittent capacity (but after first subtracting the 3.5% existing capacity). The related costs are allocated to the intermittent source.<br /> <br /> ==Nuclear power==<br /> For nuclear power, the costs also consists of capital, O&amp;M and nuclear fuel costs. Similar to the renewable energy options, technology improvement nuclear power is described via a learning curve (so costs decrease with cumulative installed capacity). At the same time, fuel costs increase as a function of depletion. Fuel costs are determined on the basis of the estimated extraction costs of uranium and thorium resources, as is described in the component [[Energy supply]]. A small trade model for these fission fuels is included.<br /> <br /> ==Hydrogen generation model==<br /> The structure of the hydrogen model is similar to that of the electric power model ([[Van Ruijven et al., 2007]]). There are, however, some important differences:<br /> *The hydrogen model distinguishes the following 11 supply options: hydrogen production plants on the basis of coal, oil, natural gas and bio-energy, with and <br /> without carbon capture and storage (8 plants), hydrogen production from electrolysis, direct hydrogen production from solar thermal processes, and, finally, small methane reform plants. <br /> *For simplification, no description of preferences for different power plants is accounted for in the operational strategy. In other words, the load factor for each option equals the total production divided by the capacity for each region.<br /> *Intermittence does not play an important role, as hydrogen can be stored to some degree. Therefore, there are no equations simulating system integration.<br /> *Hydrogen can be traded. Therefore, a trade model is added, similar to the trade models for fossil fuels, as is described in the [[Energy supply]] section.<br /> <br /> &lt;references/&gt;<br /> }}</div>

JoeriOostenrijk https://models.pbl.nl/index.php?title=Energy_conversion/Description&diff=21489 2014-05-08T15:13:28Z

<p>JoeriOostenrijk: </p> <hr /> <div> [[TIMER model|TIMER]] includes two main energy conversion modules: Electric power generation and hydrogen generation. Below, electric power generation is described in detail. In addition, the key characteristics of the hydrogen generation model, which follows a similar structure, are presented.<br /> <br /> ==Electric power generation==<br /> <br /> As shown in the flowchart, two key elements of the electric power generation are the investment strategy and the operational strategy in the sector. A challenge in simulating electricity production in an aggregated model is that in reality electricity production depends on a range of complex factors, related to costs, reliance, and the time required to switch on technologies. Modelling these factors requires a high level of detail and thus {{AbbrTemplate|IAM}}s such as [[TIMER model]] concentrate on introducing a set of simplified, meta relationships ([[Hoogwijk, 2004]]; [[Van Vuuren, 2007]]). <br /> <br /> ===Total demand for new capacity===<br /> The electricity capacity required to meet the demand per region is based on a forecast of the maximum electricity demand plus a reserve margin of about 10% (including the capacity credit assigned to different forms of electricity generation). Maximum demand is calculated on the basis of an assumed monthly shape of the load duration curve (LDC) and the gross electricity demand. The latter comprises the net electricity demand from the end-use sectors plus electricity trade and transmission losses ({{AbbrTemplate|LDC}} accounts for characteristics such as cooling and lighting demand). The demand for new generation capacity is the difference between the required and existing capacity. Power plants are assumed to be replaced at the end of their lifetime, which varies from 30 to 50 years, depending on the technology and is currently fixed in the model.<br /> <br /> ===Decisions to invest in specific options ===<br /> In the model, the decision to invest in generation technologies is based on the price of electricity (in USD/kWhe) produced per technology, using a multinomial logit equation that assigns larger market shares to the lower cost options. The specific cost of each option is broken down into several categories: investment or capital cost ({{AbbrTemplate|USD/kWe); fuel cost (USD/GJ); operational and maintenance costs (O&amp;M); and other costs (see further). The exception is hydropower capacity, which is exogenously prescribed, because large hydropower plants often have additional functions such as water supply and flood control. In the equations, some constraints are added to account for limitations in supply, for example restrictions on biomass availability. The investment for each option is given as the total investment in new generation capacity and the share of each individual technology determined on the basis of price and preference.<br /> <br /> In the following step, a decision is made to invest in different generation technologies. In the model, this is done on the basis of the price of electricity (in [[HasAcronym::USD/kWhe]]) produced per technology, using a multinomial logit equation that assigns larger market shares to the lower cost options. The specific costs of each option is broken down into a number of categories: investment or capital costs (USD/kWe), fuel costs ([[HasAcronym::USD/GJ]]), operational and maintenance costs (OM) and other costs (see further). An exception is hydropower capacity, which is exogenously prescribed, because large hydropower plants often have functions other than only electricity production (e.g. water supply and flood control). In the equations, some constraints are added to account for limitations in supply (e.g. restrictions on biomass availability). The investments needed for each option are given in the form of total investment in new generation capacity and the share of each individual technology (determined on the basis of price and preference).<br /> <br /> ==Operational strategy ==<br /> For the operational strategy, the use of power plants is based on operational costs: low-cost technologies are assumed to be used most often. This implies that capital-intensive plants with low operational costs, such as those for renewable and nuclear energy, in principle, will operate as many hours as possible. To some degree, this is also true for other plants with low operational costs (e.g. coal). Therefore, the operational decision is represented by the following three steps:<br /> #First, the renewable sources PV and wind are assigned, followed by hydropower, as these options have the lowest operational costs;<br /> #Second, the peak load capacity (i.e. period of high electricity demand) is assigned on the basis of operational costs of each available plant and the ability of these plants to provide such peak load capacity; <br /> #Third, base load (i.e. period of medium to low energy demand) is assigned on the basis of the remaining capacity (after steps 1 and 2), operational costs and the ability of options to provide the base load capacity.<br /> <br /> ==Fossil-fuel and bio-energy power plants==<br /> A total of 20 different types of power plants, generating electricity using fossil fuels and bio-energy, are included. These power plants represent different combinations of (i) conventional technology; (ii) gasification and combined cycle ([[HasAcronym::CC]]) technology; (iii) combined heat and power ([[HasAcronym::CHP]]) and, (iv) carbon capture and storage ([[HasAcronym::CCS]]) ([[Hendriks et al., 2004b]]). The specific capital costs and thermal efficiencies of these types of plants are determined by exogenous assumptions that describe the technological progress of typical components of these plants:<br /> *For conventional power plants, the coal-fired plant is defined in terms of overall efficiency and investment costs. The characteristics of all other conventional plants (using oil, natural gas or bio-energy) here are described in the investment differences for desulphurisation, fuel handling and efficiency.<br /> *For Combined Cycle (CC) power plants, the characteristics of a natural gas fuelled plant is set asthe standard. Other such plants (fuelled by oil, bio-energy and coal) are defined by indicating additional capital costs for gasification, efficiency losses due to gasification, and operation and maintenance ([[HasAcronym::O &amp; M]]) costs for fuel handling. <br /> *Power plants with carbon-capture-and-storage systems (CCS) are assumed to be CC plants, but with fuel-specific lower efficiency and higher investment and O&amp;M costs (related to capture and storage). <br /> *The characteristics of combined-heat-and-power plants (CHP) are similar to those of other plants, but with an assumed small increase in capital costs, in combination with a lower efficiency for electric conversion and an added factor for heat efficiency. <br /> <br /> The costs of one unit of electricity generated in these plants is equal to the sum of the capital costs, operation and maintenance costs (O&amp;M), fuel costs, and CO2 storage costs. <br /> <br /> ==Solar and wind power==<br /> <br /> {{FormulaAndTableTemplate|Formula1_ED}}<br /> <br /> The costs of solar and wind power are the model determined by learning and depletion dynamics. For renewable energy, costs relate to capital, O&amp;M and system integration. The capital costs mostly relate to [[Energy conversion/Description/Technical learning|learning]] and depletion processes (learning is represented by so-called learning curves; depletion is represented by long-term cost–supply curves). <br /> <br /> The additional system integration costs relate to <br /> # Discarded electricity in cases where production exceeds demand and the overcapacity cannot be used within the system;<br /> # Back-up capacity;<br /> # Additional required spinning reserve;<br /> The two last items are needed to avoid loss of power if the supply of wind or solar power suddenly drops, enabling a power scale up in a relatively short time, in power stations operating below maximum capacity ([[Hoogwijk, 2004]]).<br /> *To determine discarded electricity, the model makes a comparison between 10 different points on the load-demand curve, at the overlap between demand and supply. For both wind and solar power, a typical load–supply curve is assumed (see [[Hoogwijk, 2004]]). If supply exceeds demand, the overcapacity in electricity is assumed to be discarded, resulting in higher production costs. <br /> *Because wind and solar power supply is intermittent (i.e. it varies and therefore is not reliable), the model assumes that so-called back-up capacity needs to be installed. For the first 5% penetration of the intermittent capacity, it is assumed that no-back is required. However, for higher levels of penetration, the effective capacity (i.e. degree to which operators can rely on plants producing at a particular moment in time) of intermittent resources is assumed to decrease (referred to as the capacity factor). This decrease leads to the need of back-up power(by low-cost options, such as gas turbines), the costs of which are allocated to the intermittent source.<br /> *The required spinning reserve of the power system (capacity that can be used to respond to a rapid increase in demand) is assumed to be 3.5% of the installed capacity of a conventional power plant. If wind and solar power further penetrate the market, the model assumes an additional, required spinning reserve of 15% of the intermittent capacity (but after first subtracting the 3.5% existing capacity). The related costs are allocated to the intermittent source.<br /> <br /> ==Nuclear power==<br /> For nuclear power, the costs also consists of capital, O&amp;M and nuclear fuel costs. Similar to the renewable energy options, technology improvement nuclear power is described via a learning curve (so costs decrease with cumulative installed capacity). At the same time, fuel costs increase as a function of depletion. Fuel costs are determined on the basis of the estimated extraction costs of uranium and thorium resources, as is described in the component [[Energy supply]]. A small trade model for these fission fuels is included.<br /> <br /> ==Hydrogen generation model==<br /> The structure of the hydrogen model is similar to that of the electric power model ([[Van Ruijven et al., 2007]]). There are, however, some important differences:<br /> *The hydrogen model distinguishes the following 11 supply options: hydrogen production plants on the basis of coal, oil, natural gas and bio-energy, with and <br /> without carbon capture and storage (8 plants), hydrogen production from electrolysis, direct hydrogen production from solar thermal processes, and, finally, small methane reform plants. <br /> *For simplification, no description of preferences for different power plants is accounted for in the operational strategy. In other words, the load factor for each option equals the total production divided by the capacity for each region.<br /> *Intermittence does not play an important role, as hydrogen can be stored to some degree. Therefore, there are no equations simulating system integration.<br /> *Hydrogen can be traded. Therefore, a trade model is added, similar to the trade models for fossil fuels, as is described in the [[Energy supply]] section.<br /> <br /> &lt;references/&gt;<br /> }}</div>

JoeriOostenrijk https://models.pbl.nl/index.php?title=Energy_conversion/Description&diff=21488 2014-05-08T15:12:32Z

<p>JoeriOostenrijk: </p> <hr /> <div>{{ComponentDescriptionTemplate<br /> <br /> |Reference=Hoogwijk, 2004; Van Vuuren, 2007; Hendriks et al., 2004b; Van Ruijven et al., 2007;<br /> |Description=The [[TIMER model]] includes two energy conversion submodels: the electric power generation model and the hydrogen generation model. Here, the focus is on a description of the electric power generation model (The flowdiagram on the right also shows only the electricity model). The hydrogen model follows a similar structure, and its key characteristics are briefly discussed in this Section. <br /> <br /> <br /> ==Electric power generation==<br /> <br /> As shown in the flowchart, two key elements of the electric power generation are the investment strategy and the operational strategy in the sector. A challenge in simulating electricity production in an aggregated model is that in reality electricity production depends on a range of complex factors, related to costs, reliance, and the time required to switch on technologies. Modelling these factors requires a high level of detail and thus {{AbbrTemplate|IAM}}s such as [[TIMER model]] concentrate on introducing a set of simplified, meta relationships ([[Hoogwijk, 2004]]; [[Van Vuuren, 2007]]). <br /> <br /> ===Total demand for new capacity===<br /> The electricity capacity required to meet the demand per region is based on a forecast of the maximum electricity demand plus a reserve margin of about 10% (including the capacity credit assigned to different forms of electricity generation). Maximum demand is calculated on the basis of an assumed monthly shape of the load duration curve (LDC) and the gross electricity demand. The latter comprises the net electricity demand from the end-use sectors plus electricity trade and transmission losses ({{AbbrTemplate|LDC}} accounts for characteristics such as cooling and lighting demand). The demand for new generation capacity is the difference between the required and existing capacity. Power plants are assumed to be replaced at the end of their lifetime, which varies from 30 to 50 years, depending on the technology and is currently fixed in the model.<br /> <br /> ===Decisions to invest in specific options ===<br /> In the model, the decision to invest in generation technologies is based on the price of electricity (in USD/kWhe) produced per technology, using a multinomial logit equation that assigns larger market shares to the lower cost options. The specific cost of each option is broken down into several categories: investment or capital cost ({{AbbrTemplate|USD/kWe); fuel cost (USD/GJ); operational and maintenance costs (O&amp;M); and other costs (see further). The exception is hydropower capacity, which is exogenously prescribed, because large hydropower plants often have additional functions such as water supply and flood control. In the equations, some constraints are added to account for limitations in supply, for example restrictions on biomass availability. The investment for each option is given as the total investment in new generation capacity and the share of each individual technology determined on the basis of price and preference.<br /> <br /> In the following step, a decision is made to invest in different generation technologies. In the model, this is done on the basis of the price of electricity (in [[HasAcronym::USD/kWhe]]) produced per technology, using a multinomial logit equation that assigns larger market shares to the lower cost options. The specific costs of each option is broken down into a number of categories: investment or capital costs (USD/kWe), fuel costs ([[HasAcronym::USD/GJ]]), operational and maintenance costs (OM) and other costs (see further). An exception is hydropower capacity, which is exogenously prescribed, because large hydropower plants often have functions other than only electricity production (e.g. water supply and flood control). In the equations, some constraints are added to account for limitations in supply (e.g. restrictions on biomass availability). The investments needed for each option are given in the form of total investment in new generation capacity and the share of each individual technology (determined on the basis of price and preference).<br /> <br /> ==Operational strategy ==<br /> For the operational strategy, the use of power plants is based on operational costs: low-cost technologies are assumed to be used most often. This implies that capital-intensive plants with low operational costs, such as those for renewable and nuclear energy, in principle, will operate as many hours as possible. To some degree, this is also true for other plants with low operational costs (e.g. coal). Therefore, the operational decision is represented by the following three steps:<br /> #First, the renewable sources PV and wind are assigned, followed by hydropower, as these options have the lowest operational costs;<br /> #Second, the peak load capacity (i.e. period of high electricity demand) is assigned on the basis of operational costs of each available plant and the ability of these plants to provide such peak load capacity; <br /> #Third, base load (i.e. period of medium to low energy demand) is assigned on the basis of the remaining capacity (after steps 1 and 2), operational costs and the ability of options to provide the base load capacity.<br /> <br /> ==Fossil-fuel and bio-energy power plants==<br /> A total of 20 different types of power plants, generating electricity using fossil fuels and bio-energy, are included. These power plants represent different combinations of (i) conventional technology; (ii) gasification and combined cycle ([[HasAcronym::CC]]) technology; (iii) combined heat and power ([[HasAcronym::CHP]]) and, (iv) carbon capture and storage ([[HasAcronym::CCS]]) ([[Hendriks et al., 2004b]]). The specific capital costs and thermal efficiencies of these types of plants are determined by exogenous assumptions that describe the technological progress of typical components of these plants:<br /> *For conventional power plants, the coal-fired plant is defined in terms of overall efficiency and investment costs. The characteristics of all other conventional plants (using oil, natural gas or bio-energy) here are described in the investment differences for desulphurisation, fuel handling and efficiency.<br /> *For Combined Cycle (CC) power plants, the characteristics of a natural gas fuelled plant is set asthe standard. Other such plants (fuelled by oil, bio-energy and coal) are defined by indicating additional capital costs for gasification, efficiency losses due to gasification, and operation and maintenance ([[HasAcronym::O &amp; M]]) costs for fuel handling. <br /> *Power plants with carbon-capture-and-storage systems (CCS) are assumed to be CC plants, but with fuel-specific lower efficiency and higher investment and O&amp;M costs (related to capture and storage). <br /> *The characteristics of combined-heat-and-power plants (CHP) are similar to those of other plants, but with an assumed small increase in capital costs, in combination with a lower efficiency for electric conversion and an added factor for heat efficiency. <br /> <br /> The costs of one unit of electricity generated in these plants is equal to the sum of the capital costs, operation and maintenance costs (O&amp;M), fuel costs, and CO2 storage costs. <br /> <br /> ==Solar and wind power==<br /> <br /> {{FormulaAndTableTemplate|Formula1_ED}}<br /> <br /> The costs of solar and wind power are the model determined by learning and depletion dynamics. For renewable energy, costs relate to capital, O&amp;M and system integration. The capital costs mostly relate to [[Energy conversion/Description/Technical learning|learning]] and depletion processes (learning is represented by so-called learning curves; depletion is represented by long-term cost–supply curves). <br /> <br /> The additional system integration costs relate to <br /> # Discarded electricity in cases where production exceeds demand and the overcapacity cannot be used within the system;<br /> # Back-up capacity;<br /> # Additional required spinning reserve;<br /> The two last items are needed to avoid loss of power if the supply of wind or solar power suddenly drops, enabling a power scale up in a relatively short time, in power stations operating below maximum capacity ([[Hoogwijk, 2004]]).<br /> *To determine discarded electricity, the model makes a comparison between 10 different points on the load-demand curve, at the overlap between demand and supply. For both wind and solar power, a typical load–supply curve is assumed (see [[Hoogwijk, 2004]]). If supply exceeds demand, the overcapacity in electricity is assumed to be discarded, resulting in higher production costs. <br /> *Because wind and solar power supply is intermittent (i.e. it varies and therefore is not reliable), the model assumes that so-called back-up capacity needs to be installed. For the first 5% penetration of the intermittent capacity, it is assumed that no-back is required. However, for higher levels of penetration, the effective capacity (i.e. degree to which operators can rely on plants producing at a particular moment in time) of intermittent resources is assumed to decrease (referred to as the capacity factor). This decrease leads to the need of back-up power(by low-cost options, such as gas turbines), the costs of which are allocated to the intermittent source.<br /> *The required spinning reserve of the power system (capacity that can be used to respond to a rapid increase in demand) is assumed to be 3.5% of the installed capacity of a conventional power plant. If wind and solar power further penetrate the market, the model assumes an additional, required spinning reserve of 15% of the intermittent capacity (but after first subtracting the 3.5% existing capacity). The related costs are allocated to the intermittent source.<br /> <br /> ==Nuclear power==<br /> For nuclear power, the costs also consists of capital, O&amp;M and nuclear fuel costs. Similar to the renewable energy options, technology improvement nuclear power is described via a learning curve (so costs decrease with cumulative installed capacity). At the same time, fuel costs increase as a function of depletion. Fuel costs are determined on the basis of the estimated extraction costs of uranium and thorium resources, as is described in the component [[Energy supply]]. A small trade model for these fission fuels is included.<br /> <br /> ==Hydrogen generation model==<br /> The structure of the hydrogen model is similar to that of the electric power model ([[Van Ruijven et al., 2007]]). There are, however, some important differences:<br /> *The hydrogen model distinguishes the following 11 supply options: hydrogen production plants on the basis of coal, oil, natural gas and bio-energy, with and <br /> without carbon capture and storage (8 plants), hydrogen production from electrolysis, direct hydrogen production from solar thermal processes, and, finally, small methane reform plants. <br /> *For simplification, no description of preferences for different power plants is accounted for in the operational strategy. In other words, the load factor for each option equals the total production divided by the capacity for each region.<br /> *Intermittence does not play an important role, as hydrogen can be stored to some degree. Therefore, there are no equations simulating system integration.<br /> *Hydrogen can be traded. Therefore, a trade model is added, similar to the trade models for fossil fuels, as is described in the [[Energy supply]] section.<br /> <br /> &lt;references/&gt;<br /> }}</div>

JoeriOostenrijk https://models.pbl.nl/index.php?title=Energy_conversion/Description&diff=21487 2014-05-08T15:00:36Z

<p>JoeriOostenrijk: </p> <hr /> <div>{{ComponentDescriptionTemplate|Reference=Hoogwijk, 2004; Van Vuuren, 2007; Hendriks et al., 2004b; Van Ruijven et al., 2007;<br /> |Description=[[TIMER model]] includes two main energy conversion modules: Electric power generation and hydrogen generation. Below, electric power generation is described in detail. In addition, the key characteristics of the hydrogen generation model, which follows a similar structure, are presented.<br /> <br /> ==Electric power generation==<br /> <br /> As shown in the flowchart, two key elements of the electric power generation are the investment strategy and the operational strategy in the sector. A challenge in simulating electricity production in an aggregated model is that in reality electricity production depends on a range of complex factors, related to costs, reliance, and the time required to switch on technologies. Modelling these factors requires a high level of detail and thus {{AbbrTemplate|IAM}}s such as [[TIMER model]] concentrate on introducing a set of simplified, meta relationships ([[Hoogwijk, 2004]]; [[Van Vuuren, 2007]]). <br /> <br /> ===Total demand for new capacity===<br /> The electricity capacity required to meet the demand per region is based on a forecast of the maximum electricity demand plus a reserve margin of about 10% (including the capacity credit assigned to different forms of electricity generation). Maximum demand is calculated on the basis of an assumed monthly shape of the load duration curve (LDC) and the gross electricity demand. The latter comprises the net electricity demand from the end-use sectors plus electricity trade and transmission losses ({{AbbrTemplate|LDC}} accounts for characteristics such as cooling and lighting demand). The demand for new generation capacity is the difference between the required and existing capacity. Power plants are assumed to be replaced at the end of their lifetime, which varies from 30 to 50 years, depending on the technology and is currently fixed in the model.<br /> <br /> ===Decisions to invest in specific options ===<br /> In the model, the decision to invest in generation technologies is based on the price of electricity (in USD/kWhe) produced per technology, using a multinomial logit equation that assigns larger market shares to the lower cost options. The specific cost of each option is broken down into several categories: investment or capital cost ({{AbbrTemplate|USD/kWe); fuel cost (USD/GJ); operational and maintenance costs (O&amp;M); and other costs (see further). The exception is hydropower capacity, which is exogenously prescribed, because large hydropower plants often have additional functions such as water supply and flood control. In the equations, some constraints are added to account for limitations in supply, for example restrictions on biomass availability. The investment for each option is given as the total investment in new generation capacity and the share of each individual technology determined on the basis of price and preference.<br /> <br /> In the following step, a decision is made to invest in different generation technologies. In the model, this is done on the basis of the price of electricity (in [[HasAcronym::USD/kWhe]]) produced per technology, using a multinomial logit equation that assigns larger market shares to the lower cost options. The specific costs of each option is broken down into a number of categories: investment or capital costs (USD/kWe), fuel costs ([[HasAcronym::USD/GJ]]), operational and maintenance costs (OM) and other costs (see further). An exception is hydropower capacity, which is exogenously prescribed, because large hydropower plants often have functions other than only electricity production (e.g. water supply and flood control). In the equations, some constraints are added to account for limitations in supply (e.g. restrictions on biomass availability). The investments needed for each option are given in the form of total investment in new generation capacity and the share of each individual technology (determined on the basis of price and preference).<br /> <br /> ==Operational strategy ==<br /> For the operational strategy, the use of power plants is based on operational costs: low-cost technologies are assumed to be used most often. This implies that capital-intensive plants with low operational costs, such as those for renewable and nuclear energy, in principle, will operate as many hours as possible. To some degree, this is also true for other plants with low operational costs (e.g. coal). Therefore, the operational decision is represented by the following three steps:<br /> #First, the renewable sources PV and wind are assigned, followed by hydropower, as these options have the lowest operational costs;<br /> #Second, the peak load capacity (i.e. period of high electricity demand) is assigned on the basis of operational costs of each available plant and the ability of these plants to provide such peak load capacity; <br /> #Third, base load (i.e. period of medium to low energy demand) is assigned on the basis of the remaining capacity (after steps 1 and 2), operational costs and the ability of options to provide the base load capacity.<br /> <br /> ==Fossil-fuel and bio-energy power plants==<br /> A total of 20 different types of power plants, generating electricity using fossil fuels and bio-energy, are included. These power plants represent different combinations of (i) conventional technology; (ii) gasification and combined cycle ([[HasAcronym::CC]]) technology; (iii) combined heat and power ([[HasAcronym::CHP]]) and, (iv) carbon capture and storage ([[HasAcronym::CCS]]) ([[Hendriks et al., 2004b]]). The specific capital costs and thermal efficiencies of these types of plants are determined by exogenous assumptions that describe the technological progress of typical components of these plants:<br /> *For conventional power plants, the coal-fired plant is defined in terms of overall efficiency and investment costs. The characteristics of all other conventional plants (using oil, natural gas or bio-energy) here are described in the investment differences for desulphurisation, fuel handling and efficiency.<br /> *For Combined Cycle (CC) power plants, the characteristics of a natural gas fuelled plant is set asthe standard. Other such plants (fuelled by oil, bio-energy and coal) are defined by indicating additional capital costs for gasification, efficiency losses due to gasification, and operation and maintenance ([[HasAcronym::O &amp; M]]) costs for fuel handling. <br /> *Power plants with carbon-capture-and-storage systems (CCS) are assumed to be CC plants, but with fuel-specific lower efficiency and higher investment and O&amp;M costs (related to capture and storage). <br /> *The characteristics of combined-heat-and-power plants (CHP) are similar to those of other plants, but with an assumed small increase in capital costs, in combination with a lower efficiency for electric conversion and an added factor for heat efficiency. <br /> <br /> The costs of one unit of electricity generated in these plants is equal to the sum of the capital costs, operation and maintenance costs (O&amp;M), fuel costs, and CO2 storage costs. <br /> <br /> ==Solar and wind power==<br /> <br /> {{FormulaAndTableTemplate|Formula1_ED}}<br /> <br /> The costs of solar and wind power are the model determined by learning and depletion dynamics. For renewable energy, costs relate to capital, O&amp;M and system integration. The capital costs mostly relate to [[Energy conversion/Description/Technical learning|learning]] and depletion processes (learning is represented by so-called learning curves; depletion is represented by long-term cost–supply curves). <br /> <br /> The additional system integration costs relate to <br /> # Discarded electricity in cases where production exceeds demand and the overcapacity cannot be used within the system;<br /> # Back-up capacity;<br /> # Additional required spinning reserve;<br /> The two last items are needed to avoid loss of power if the supply of wind or solar power suddenly drops, enabling a power scale up in a relatively short time, in power stations operating below maximum capacity ([[Hoogwijk, 2004]]).<br /> *To determine discarded electricity, the model makes a comparison between 10 different points on the load-demand curve, at the overlap between demand and supply. For both wind and solar power, a typical load–supply curve is assumed (see [[Hoogwijk, 2004]]). If supply exceeds demand, the overcapacity in electricity is assumed to be discarded, resulting in higher production costs. <br /> *Because wind and solar power supply is intermittent (i.e. it varies and therefore is not reliable), the model assumes that so-called back-up capacity needs to be installed. For the first 5% penetration of the intermittent capacity, it is assumed that no-back is required. However, for higher levels of penetration, the effective capacity (i.e. degree to which operators can rely on plants producing at a particular moment in time) of intermittent resources is assumed to decrease (referred to as the capacity factor). This decrease leads to the need of back-up power(by low-cost options, such as gas turbines), the costs of which are allocated to the intermittent source.<br /> *The required spinning reserve of the power system (capacity that can be used to respond to a rapid increase in demand) is assumed to be 3.5% of the installed capacity of a conventional power plant. If wind and solar power further penetrate the market, the model assumes an additional, required spinning reserve of 15% of the intermittent capacity (but after first subtracting the 3.5% existing capacity). The related costs are allocated to the intermittent source.<br /> <br /> ==Nuclear power==<br /> For nuclear power, the costs also consists of capital, O&amp;M and nuclear fuel costs. Similar to the renewable energy options, technology improvement nuclear power is described via a learning curve (so costs decrease with cumulative installed capacity). At the same time, fuel costs increase as a function of depletion. Fuel costs are determined on the basis of the estimated extraction costs of uranium and thorium resources, as is described in the component [[Energy supply]]. A small trade model for these fission fuels is included.<br /> <br /> ==Hydrogen generation model==<br /> The structure of the hydrogen model is similar to that of the electric power model ([[Van Ruijven et al., 2007]]). There are, however, some important differences:<br /> *The hydrogen model distinguishes the following 11 supply options: hydrogen production plants on the basis of coal, oil, natural gas and bio-energy, with and <br /> without carbon capture and storage (8 plants), hydrogen production from electrolysis, direct hydrogen production from solar thermal processes, and, finally, small methane reform plants. <br /> *For simplification, no description of preferences for different power plants is accounted for in the operational strategy. In other words, the load factor for each option equals the total production divided by the capacity for each region.<br /> *Intermittence does not play an important role, as hydrogen can be stored to some degree. Therefore, there are no equations simulating system integration.<br /> *Hydrogen can be traded. Therefore, a trade model is added, similar to the trade models for fossil fuels, as is described in the [[Energy supply]] section.<br /> <br /> &lt;references/&gt;<br /> }}</div>

JoeriOostenrijk https://models.pbl.nl/index.php?title=Energy_conversion/Description&diff=21486 2014-05-08T14:56:15Z

<p>JoeriOostenrijk: </p> <hr /> <div>{{ComponentDescriptionTemplate<br /> |Reference=Hoogwijk, 2004; Van Vuuren, 2007; Hendriks et al., 2004b; Van Ruijven et al., 2007;<br /> |Description=[[TIMER model]] includes two main energy conversion modules: Electric power generation and hydrogen generation. Below, electric power generation is described in detail. In addition, the key characteristics of the hydrogen generation model, which follows a similar structure, are presented.<br /> <br /> ==Electric power generation==<br /> <br /> As shown in the flowchart, two key elements of the electric power generation are the investment strategy and the operational strategy in the sector. A challenge in simulating electricity production in an aggregated model is that in reality electricity production depends on a range of complex factors, related to costs, reliance, and the time required to switch on technologies. Modelling these factors requires a high level of detail and thus {{AbbrTemplate|IAM}}s such as [[TIMER model]] concentrate on introducing a set of simplified, meta relationships ([[Hoogwijk, 2004]]; [[Van Vuuren, 2007]]). <br /> <br /> ===Total demand for new capacity===<br /> The electricity capacity required to meet the demand per region is based on a forecast of the maximum electricity demand plus a reserve margin of about 10% (including the capacity credit assigned to different forms of electricity generation). Maximum demand is calculated on the basis of an assumed monthly shape of the load duration curve (LDC) and the gross electricity demand. The latter comprises the net electricity demand from the end-use sectors plus electricity trade and transmission losses ({{AbbrTemplate|LDC}} accounts for characteristics such as cooling and lighting demand). The demand for new generation capacity is the difference between the required and existing capacity. Power plants are assumed to be replaced at the end of their lifetime, which varies from 30 to 50 years, depending on the technology and is currently fixed in the model.<br /> <br /> ===Decisions to invest in specific options ===<br /> In the model, the decision to invest in generation technologies is based on the price of electricity (in USD/kWhe) produced per technology, using a multinomial logit equation that assigns larger market shares to the lower cost options. The specific cost of each option is broken down into several categories: investment or capital cost ({{AbbrTemplate|USD/kWe); fuel cost (USD/GJ); operational and maintenance costs (O&amp;M); and other costs (see further). The exception is hydropower capacity, which is exogenously prescribed, because large hydropower plants often have additional functions such as water supply and flood control. In the equations, some constraints are added to account for limitations in supply, for example restrictions on biomass availability. The investment for each option is given as the total investment in new generation capacity and the share of each individual technology determined on the basis of price and preference.<br /> <br /> In the following step, a decision is made to invest in different generation technologies. In the model, this is done on the basis of the price of electricity (in [[HasAcronym::USD/kWhe]]) produced per technology, using a multinomial logit equation that assigns larger market shares to the lower cost options. The specific costs of each option is broken down into a number of categories: investment or capital costs (USD/kWe), fuel costs ([[HasAcronym::USD/GJ]]), operational and maintenance costs (OM) and other costs (see further). An exception is hydropower capacity, which is exogenously prescribed, because large hydropower plants often have functions other than only electricity production (e.g. water supply and flood control). In the equations, some constraints are added to account for limitations in supply (e.g. restrictions on biomass availability). The investments needed for each option are given in the form of total investment in new generation capacity and the share of each individual technology (determined on the basis of price and preference).<br /> <br /> ==Operational strategy ==<br /> For the operational strategy, the use of power plants is based on operational costs: low-cost technologies are assumed to be used most often. This implies that capital-intensive plants with low operational costs, such as those for renewable and nuclear energy, in principle, will operate as many hours as possible. To some degree, this is also true for other plants with low operational costs (e.g. coal). Therefore, the operational decision is represented by the following three steps:<br /> #First, the renewable sources PV and wind are assigned, followed by hydropower, as these options have the lowest operational costs;<br /> #Second, the peak load capacity (i.e. period of high electricity demand) is assigned on the basis of operational costs of each available plant and the ability of these plants to provide such peak load capacity; <br /> #Third, base load (i.e. period of medium to low energy demand) is assigned on the basis of the remaining capacity (after steps 1 and 2), operational costs and the ability of options to provide the base load capacity.<br /> <br /> ==Fossil-fuel and bio-energy power plants==<br /> A total of 20 different types of power plants, generating electricity using fossil fuels and bio-energy, are included. These power plants represent different combinations of (i) conventional technology; (ii) gasification and combined cycle ([[HasAcronym::CC]]) technology; (iii) combined heat and power ([[HasAcronym::CHP]]) and, (iv) carbon capture and storage ([[HasAcronym::CCS]]) ([[Hendriks et al., 2004b]]). The specific capital costs and thermal efficiencies of these types of plants are determined by exogenous assumptions that describe the technological progress of typical components of these plants:<br /> *For conventional power plants, the coal-fired plant is defined in terms of overall efficiency and investment costs. The characteristics of all other conventional plants (using oil, natural gas or bio-energy) here are described in the investment differences for desulphurisation, fuel handling and efficiency.<br /> *For Combined Cycle (CC) power plants, the characteristics of a natural gas fuelled plant is set asthe standard. Other such plants (fuelled by oil, bio-energy and coal) are defined by indicating additional capital costs for gasification, efficiency losses due to gasification, and operation and maintenance ([[HasAcronym::O &amp; M]]) costs for fuel handling. <br /> *Power plants with carbon-capture-and-storage systems (CCS) are assumed to be CC plants, but with fuel-specific lower efficiency and higher investment and O&amp;M costs (related to capture and storage). <br /> *The characteristics of combined-heat-and-power plants (CHP) are similar to those of other plants, but with an assumed small increase in capital costs, in combination with a lower efficiency for electric conversion and an added factor for heat efficiency. <br /> <br /> The costs of one unit of electricity generated in these plants is equal to the sum of the capital costs, operation and maintenance costs (O&amp;M), fuel costs, and CO2 storage costs. <br /> <br /> ==Solar and wind power==<br /> <br /> {{FormulaAndTableTemplate|Formula1_ED}}<br /> <br /> The costs of solar and wind power are the model determined by learning and depletion dynamics. For renewable energy, costs relate to capital, O&amp;M and system integration. The capital costs mostly relate to [[Energy conversion/Description/Technical learning|learning]] and depletion processes (learning is represented by so-called learning curves; depletion is represented by long-term cost–supply curves). <br /> <br /> The additional system integration costs relate to <br /> # Discarded electricity in cases where production exceeds demand and the overcapacity cannot be used within the system;<br /> # Back-up capacity;<br /> # Additional required spinning reserve;<br /> The two last items are needed to avoid loss of power if the supply of wind or solar power suddenly drops, enabling a power scale up in a relatively short time, in power stations operating below maximum capacity ([[Hoogwijk, 2004]]).<br /> *To determine discarded electricity, the model makes a comparison between 10 different points on the load-demand curve, at the overlap between demand and supply. For both wind and solar power, a typical load–supply curve is assumed (see [[Hoogwijk, 2004]]). If supply exceeds demand, the overcapacity in electricity is assumed to be discarded, resulting in higher production costs. <br /> *Because wind and solar power supply is intermittent (i.e. it varies and therefore is not reliable), the model assumes that so-called back-up capacity needs to be installed. For the first 5% penetration of the intermittent capacity, it is assumed that no-back is required. However, for higher levels of penetration, the effective capacity (i.e. degree to which operators can rely on plants producing at a particular moment in time) of intermittent resources is assumed to decrease (referred to as the capacity factor). This decrease leads to the need of back-up power(by low-cost options, such as gas turbines), the costs of which are allocated to the intermittent source.<br /> *The required spinning reserve of the power system (capacity that can be used to respond to a rapid increase in demand) is assumed to be 3.5% of the installed capacity of a conventional power plant. If wind and solar power further penetrate the market, the model assumes an additional, required spinning reserve of 15% of the intermittent capacity (but after first subtracting the 3.5% existing capacity). The related costs are allocated to the intermittent source.<br /> <br /> ==Nuclear power==<br /> For nuclear power, the costs also consists of capital, O&amp;M and nuclear fuel costs. Similar to the renewable energy options, technology improvement nuclear power is described via a learning curve (so costs decrease with cumulative installed capacity). At the same time, fuel costs increase as a function of depletion. Fuel costs are determined on the basis of the estimated extraction costs of uranium and thorium resources, as is described in the component [[Energy supply]]. A small trade model for these fission fuels is included.<br /> <br /> ==Hydrogen generation model==<br /> The structure of the hydrogen model is similar to that of the electric power model ([[Van Ruijven et al., 2007]]). There are, however, some important differences:<br /> *The hydrogen model distinguishes the following 11 supply options: hydrogen production plants on the basis of coal, oil, natural gas and bio-energy, with and <br /> without carbon capture and storage (8 plants), hydrogen production from electrolysis, direct hydrogen production from solar thermal processes, and, finally, small methane reform plants. <br /> *For simplification, no description of preferences for different power plants is accounted for in the operational strategy. In other words, the load factor for each option equals the total production divided by the capacity for each region.<br /> *Intermittence does not play an important role, as hydrogen can be stored to some degree. Therefore, there are no equations simulating system integration.<br /> *Hydrogen can be traded. Therefore, a trade model is added, similar to the trade models for fossil fuels, as is described in the [[Energy supply]] section.<br /> <br /> &lt;references/&gt;<br /> }}</div>

JoeriOostenrijk https://models.pbl.nl/index.php?title=Energy_conversion/Description&diff=21485 2014-05-08T14:50:45Z

<p>JoeriOostenrijk: </p> <hr /> <div>{{ComponentDescriptionTemplate<br /> |Reference=Hoogwijk, 2004; Van Vuuren, 2007; Hendriks et al., 2004b; Van Ruijven et al., 2007;<br /> |Description=[[TIMER model]] includes two main energy conversion modules: Electric power generation and hydrogen generation. Below, electric power generation is described in detail. In addition, the key characteristics of the hydrogen generation model, which follows a similar structure, are presented.<br /> <br /> ==Electric power generation==<br /> <br /> As shown in the flowchart, two key elements of the electric power generation are the investment strategy and the operational strategy in the sector. A challenge in simulating electricity production in an aggregated model is that in reality electricity production depends on a range of complex factors, related to costs, reliance, and the time required to switch on technologies. Modelling these factors requires a high level of detail and thus {{AbbrTemplate|IAM}}s such as [[TIMER model]] concentrate on introducing a set of simplified, meta relationships ([[Hoogwijk, 2004]]; [[Van Vuuren, 2007]]). <br /> <br /> <br /> ===Total demand for new capacity===<br /> The electricity capacity required to meet the demand per region is based on a forecast of the maximum electricity demand plus a reserve margin of about 10% (including the capacity credit assigned to different forms of electricity generation). Maximum demand is calculated on the basis of an assumed monthly shape of the load duration curve (LDC) and the gross electricity demand. The latter comprises the net electricity demand from the end-use sectors plus electricity trade and transmission losses ({{AbbrTemplate|LDC}} accounts for characteristics such as cooling and lighting demand). The demand for new generation capacity is the difference between the required and existing capacity. Power plants are assumed to be replaced at the end of their lifetime, which varies from 30 to 50 years, depending on the technology and is currently fixed in the model..<br /> <br /> ===Decisions to invest in specific options ===<br /> In the following step, a decision is made to invest in different generation technologies. In the model, this is done on the basis of the price of electricity (in [[HasAcronym::USD/kWhe]]) produced per technology, using a multinomial logit equation that assigns larger market shares to the lower cost options. The specific costs of each option is broken down into a number of categories: investment or capital costs (USD/kWe), fuel costs ([[HasAcronym::USD/GJ]]), operational and maintenance costs (OM) and other costs (see further). An exception is hydropower capacity, which is exogenously prescribed, because large hydropower plants often have functions other than only electricity production (e.g. water supply and flood control). In the equations, some constraints are added to account for limitations in supply (e.g. restrictions on biomass availability). The investments needed for each option are given in the form of total investment in new generation capacity and the share of each individual technology (determined on the basis of price and preference).<br /> <br /> ==Operational strategy ==<br /> For the operational strategy, the use of power plants is based on operational costs: low-cost technologies are assumed to be used most often. This implies that capital-intensive plants with low operational costs, such as those for renewable and nuclear energy, in principle, will operate as many hours as possible. To some degree, this is also true for other plants with low operational costs (e.g. coal). Therefore, the operational decision is represented by the following three steps:<br /> #First, the renewable sources PV and wind are assigned, followed by hydropower, as these options have the lowest operational costs;<br /> #Second, the peak load capacity (i.e. period of high electricity demand) is assigned on the basis of operational costs of each available plant and the ability of these plants to provide such peak load capacity; <br /> #Third, base load (i.e. period of medium to low energy demand) is assigned on the basis of the remaining capacity (after steps 1 and 2), operational costs and the ability of options to provide the base load capacity.<br /> <br /> ==Fossil-fuel and bio-energy power plants==<br /> A total of 20 different types of power plants, generating electricity using fossil fuels and bio-energy, are included. These power plants represent different combinations of (i) conventional technology; (ii) gasification and combined cycle ([[HasAcronym::CC]]) technology; (iii) combined heat and power ([[HasAcronym::CHP]]) and, (iv) carbon capture and storage ([[HasAcronym::CCS]]) ([[Hendriks et al., 2004b]]). The specific capital costs and thermal efficiencies of these types of plants are determined by exogenous assumptions that describe the technological progress of typical components of these plants:<br /> *For conventional power plants, the coal-fired plant is defined in terms of overall efficiency and investment costs. The characteristics of all other conventional plants (using oil, natural gas or bio-energy) here are described in the investment differences for desulphurisation, fuel handling and efficiency.<br /> *For Combined Cycle (CC) power plants, the characteristics of a natural gas fuelled plant is set asthe standard. Other such plants (fuelled by oil, bio-energy and coal) are defined by indicating additional capital costs for gasification, efficiency losses due to gasification, and operation and maintenance ([[HasAcronym::O &amp; M]]) costs for fuel handling. <br /> *Power plants with carbon-capture-and-storage systems (CCS) are assumed to be CC plants, but with fuel-specific lower efficiency and higher investment and O&amp;M costs (related to capture and storage). <br /> *The characteristics of combined-heat-and-power plants (CHP) are similar to those of other plants, but with an assumed small increase in capital costs, in combination with a lower efficiency for electric conversion and an added factor for heat efficiency. <br /> <br /> The costs of one unit of electricity generated in these plants is equal to the sum of the capital costs, operation and maintenance costs (O&amp;M), fuel costs, and CO2 storage costs. <br /> <br /> ==Solar and wind power==<br /> <br /> {{FormulaAndTableTemplate|Formula1_ED}}<br /> <br /> The costs of solar and wind power are the model determined by learning and depletion dynamics. For renewable energy, costs relate to capital, O&amp;M and system integration. The capital costs mostly relate to [[Energy conversion/Description/Technical learning|learning]] and depletion processes (learning is represented by so-called learning curves; depletion is represented by long-term cost–supply curves). <br /> <br /> The additional system integration costs relate to <br /> # Discarded electricity in cases where production exceeds demand and the overcapacity cannot be used within the system;<br /> # Back-up capacity;<br /> # Additional required spinning reserve;<br /> The two last items are needed to avoid loss of power if the supply of wind or solar power suddenly drops, enabling a power scale up in a relatively short time, in power stations operating below maximum capacity ([[Hoogwijk, 2004]]).<br /> *To determine discarded electricity, the model makes a comparison between 10 different points on the load-demand curve, at the overlap between demand and supply. For both wind and solar power, a typical load–supply curve is assumed (see [[Hoogwijk, 2004]]). If supply exceeds demand, the overcapacity in electricity is assumed to be discarded, resulting in higher production costs. <br /> *Because wind and solar power supply is intermittent (i.e. it varies and therefore is not reliable), the model assumes that so-called back-up capacity needs to be installed. For the first 5% penetration of the intermittent capacity, it is assumed that no-back is required. However, for higher levels of penetration, the effective capacity (i.e. degree to which operators can rely on plants producing at a particular moment in time) of intermittent resources is assumed to decrease (referred to as the capacity factor). This decrease leads to the need of back-up power(by low-cost options, such as gas turbines), the costs of which are allocated to the intermittent source.<br /> *The required spinning reserve of the power system (capacity that can be used to respond to a rapid increase in demand) is assumed to be 3.5% of the installed capacity of a conventional power plant. If wind and solar power further penetrate the market, the model assumes an additional, required spinning reserve of 15% of the intermittent capacity (but after first subtracting the 3.5% existing capacity). The related costs are allocated to the intermittent source.<br /> <br /> ==Nuclear power==<br /> For nuclear power, the costs also consists of capital, O&amp;M and nuclear fuel costs. Similar to the renewable energy options, technology improvement nuclear power is described via a learning curve (so costs decrease with cumulative installed capacity). At the same time, fuel costs increase as a function of depletion. Fuel costs are determined on the basis of the estimated extraction costs of uranium and thorium resources, as is described in the component [[Energy supply]]. A small trade model for these fission fuels is included.<br /> <br /> ==Hydrogen generation model==<br /> The structure of the hydrogen model is similar to that of the electric power model ([[Van Ruijven et al., 2007]]). There are, however, some important differences:<br /> *The hydrogen model distinguishes the following 11 supply options: hydrogen production plants on the basis of coal, oil, natural gas and bio-energy, with and <br /> without carbon capture and storage (8 plants), hydrogen production from electrolysis, direct hydrogen production from solar thermal processes, and, finally, small methane reform plants. <br /> *For simplification, no description of preferences for different power plants is accounted for in the operational strategy. In other words, the load factor for each option equals the total production divided by the capacity for each region.<br /> *Intermittence does not play an important role, as hydrogen can be stored to some degree. Therefore, there are no equations simulating system integration.<br /> *Hydrogen can be traded. Therefore, a trade model is added, similar to the trade models for fossil fuels, as is described in the [[Energy supply]] section.<br /> <br /> &lt;references/&gt;<br /> }}</div>

JoeriOostenrijk https://models.pbl.nl/index.php?title=Energy_conversion/Description&diff=21484 2014-05-08T14:48:12Z

<p>JoeriOostenrijk: </p> <hr /> <div>{{ComponentDescriptionTemplate<br /> |Reference=Hoogwijk, 2004; Van Vuuren, 2007; Hendriks et al., 2004b; Van Ruijven et al., 2007;<br /> |Description=[[TIMER model]] includes two main energy conversion modules: Electric power generation and hydrogen generation. Below, electric power generation is described in detail. In addition, the key characteristics of the hydrogen generation model, which follows a similar structure, are presented.<br /> <br /> ==Electric power generation==<br /> <br /> As shown in the flowchart, two key elements of the electric power generation are the investment strategy and the operational strategy in the sector. A challenge in simulating electricity production in an aggregated model is that in reality electricity production depends on a range of complex factors, related to costs, reliance, and the time required to switch on technologies. Modelling these factors requires a high level of detail and thus{{AbbrTemplate|IAM}}s such as [[TIMER model]] concentrate on introducing a set of simplified, meta relationships ([[Hoogwijk, 2004]]; [[Van Vuuren, 2007]]). <br /> <br /> <br /> ===Total demand for new capacity===<br /> The electricity capacity required to meet the demand per region is based on a forecast of the maximum electricity demand plus a reserve margin of about 10% (including the capacity credit assigned to different forms of electricity generation). Maximum demand is calculated on the basis of an assumed monthly shape of the load duration curve (LDC) and the gross electricity demand. The latter comprises the net electricity demand from the end-use sectors plus electricity trade and transmission losses (LDC accounts for characteristics such as cooling and lighting demand). The demand for new generation capacity is the difference between the required and existing capacity. Power plants are assumed to be replaced at the end of their lifetime, which varies from 30 to 50 years, depending on the technology and is currently fixed in the model.<br /> <br /> ===Decisions to invest in specific options ===<br /> In the following step, a decision is made to invest in different generation technologies. In the model, this is done on the basis of the price of electricity (in [[HasAcronym::USD/kWhe]]) produced per technology, using a multinomial logit equation that assigns larger market shares to the lower cost options. The specific costs of each option is broken down into a number of categories: investment or capital costs (USD/kWe), fuel costs ([[HasAcronym::USD/GJ]]), operational and maintenance costs (OM) and other costs (see further). An exception is hydropower capacity, which is exogenously prescribed, because large hydropower plants often have functions other than only electricity production (e.g. water supply and flood control). In the equations, some constraints are added to account for limitations in supply (e.g. restrictions on biomass availability). The investments needed for each option are given in the form of total investment in new generation capacity and the share of each individual technology (determined on the basis of price and preference).<br /> <br /> ==Operational strategy ==<br /> For the operational strategy, the use of power plants is based on operational costs: low-cost technologies are assumed to be used most often. This implies that capital-intensive plants with low operational costs, such as those for renewable and nuclear energy, in principle, will operate as many hours as possible. To some degree, this is also true for other plants with low operational costs (e.g. coal). Therefore, the operational decision is represented by the following three steps:<br /> #First, the renewable sources PV and wind are assigned, followed by hydropower, as these options have the lowest operational costs;<br /> #Second, the peak load capacity (i.e. period of high electricity demand) is assigned on the basis of operational costs of each available plant and the ability of these plants to provide such peak load capacity; <br /> #Third, base load (i.e. period of medium to low energy demand) is assigned on the basis of the remaining capacity (after steps 1 and 2), operational costs and the ability of options to provide the base load capacity.<br /> <br /> ==Fossil-fuel and bio-energy power plants==<br /> A total of 20 different types of power plants, generating electricity using fossil fuels and bio-energy, are included. These power plants represent different combinations of (i) conventional technology; (ii) gasification and combined cycle ([[HasAcronym::CC]]) technology; (iii) combined heat and power ([[HasAcronym::CHP]]) and, (iv) carbon capture and storage ([[HasAcronym::CCS]]) ([[Hendriks et al., 2004b]]). The specific capital costs and thermal efficiencies of these types of plants are determined by exogenous assumptions that describe the technological progress of typical components of these plants:<br /> *For conventional power plants, the coal-fired plant is defined in terms of overall efficiency and investment costs. The characteristics of all other conventional plants (using oil, natural gas or bio-energy) here are described in the investment differences for desulphurisation, fuel handling and efficiency.<br /> *For Combined Cycle (CC) power plants, the characteristics of a natural gas fuelled plant is set asthe standard. Other such plants (fuelled by oil, bio-energy and coal) are defined by indicating additional capital costs for gasification, efficiency losses due to gasification, and operation and maintenance ([[HasAcronym::O &amp; M]]) costs for fuel handling. <br /> *Power plants with carbon-capture-and-storage systems (CCS) are assumed to be CC plants, but with fuel-specific lower efficiency and higher investment and O&amp;M costs (related to capture and storage). <br /> *The characteristics of combined-heat-and-power plants (CHP) are similar to those of other plants, but with an assumed small increase in capital costs, in combination with a lower efficiency for electric conversion and an added factor for heat efficiency. <br /> <br /> The costs of one unit of electricity generated in these plants is equal to the sum of the capital costs, operation and maintenance costs (O&amp;M), fuel costs, and CO2 storage costs. <br /> <br /> ==Solar and wind power==<br /> <br /> {{FormulaAndTableTemplate|Formula1_ED}}<br /> <br /> The costs of solar and wind power are the model determined by learning and depletion dynamics. For renewable energy, costs relate to capital, O&amp;M and system integration. The capital costs mostly relate to [[Energy conversion/Description/Technical learning|learning]] and depletion processes (learning is represented by so-called learning curves; depletion is represented by long-term cost–supply curves). <br /> <br /> The additional system integration costs relate to <br /> # Discarded electricity in cases where production exceeds demand and the overcapacity cannot be used within the system;<br /> # Back-up capacity;<br /> # Additional required spinning reserve;<br /> The two last items are needed to avoid loss of power if the supply of wind or solar power suddenly drops, enabling a power scale up in a relatively short time, in power stations operating below maximum capacity ([[Hoogwijk, 2004]]).<br /> *To determine discarded electricity, the model makes a comparison between 10 different points on the load-demand curve, at the overlap between demand and supply. For both wind and solar power, a typical load–supply curve is assumed (see [[Hoogwijk, 2004]]). If supply exceeds demand, the overcapacity in electricity is assumed to be discarded, resulting in higher production costs. <br /> *Because wind and solar power supply is intermittent (i.e. it varies and therefore is not reliable), the model assumes that so-called back-up capacity needs to be installed. For the first 5% penetration of the intermittent capacity, it is assumed that no-back is required. However, for higher levels of penetration, the effective capacity (i.e. degree to which operators can rely on plants producing at a particular moment in time) of intermittent resources is assumed to decrease (referred to as the capacity factor). This decrease leads to the need of back-up power(by low-cost options, such as gas turbines), the costs of which are allocated to the intermittent source.<br /> *The required spinning reserve of the power system (capacity that can be used to respond to a rapid increase in demand) is assumed to be 3.5% of the installed capacity of a conventional power plant. If wind and solar power further penetrate the market, the model assumes an additional, required spinning reserve of 15% of the intermittent capacity (but after first subtracting the 3.5% existing capacity). The related costs are allocated to the intermittent source.<br /> <br /> ==Nuclear power==<br /> For nuclear power, the costs also consists of capital, O&amp;M and nuclear fuel costs. Similar to the renewable energy options, technology improvement nuclear power is described via a learning curve (so costs decrease with cumulative installed capacity). At the same time, fuel costs increase as a function of depletion. Fuel costs are determined on the basis of the estimated extraction costs of uranium and thorium resources, as is described in the component [[Energy supply]]. A small trade model for these fission fuels is included.<br /> <br /> ==Hydrogen generation model==<br /> The structure of the hydrogen model is similar to that of the electric power model ([[Van Ruijven et al., 2007]]). There are, however, some important differences:<br /> *The hydrogen model distinguishes the following 11 supply options: hydrogen production plants on the basis of coal, oil, natural gas and bio-energy, with and <br /> without carbon capture and storage (8 plants), hydrogen production from electrolysis, direct hydrogen production from solar thermal processes, and, finally, small methane reform plants. <br /> *For simplification, no description of preferences for different power plants is accounted for in the operational strategy. In other words, the load factor for each option equals the total production divided by the capacity for each region.<br /> *Intermittence does not play an important role, as hydrogen can be stored to some degree. Therefore, there are no equations simulating system integration.<br /> *Hydrogen can be traded. Therefore, a trade model is added, similar to the trade models for fossil fuels, as is described in the [[Energy supply]] section.<br /> <br /> &lt;references/&gt;<br /> }}</div>

JoeriOostenrijk https://models.pbl.nl/index.php?title=Energy_conversion/Description&diff=21483 2014-05-08T14:47:43Z

<p>JoeriOostenrijk: </p> <hr /> <div>{{ComponentDescriptionTemplate<br /> |Reference=Hoogwijk, 2004; Van Vuuren, 2007; Hendriks et al., 2004b; Van Ruijven et al., 2007;<br /> |Description=[[TIMER model]] includes two main energy conversion modules: Electric power generation and hydrogen generation. Below, electric power generation is described in detail. In addition, the key characteristics of the hydrogen generation model, which follows a similar structure, are presented.<br /> <br /> ==Electric power generation==<br /> <br /> As shown in the flowchart, two key elements of the electric power generation are the investment strategy and the operational strategy in the sector. A challenge in simulating electricity production in an aggregated model is that in reality electricity production depends on a range of complex factors, related to costs, reliance, and the time required to switch on technologies. Modelling these factors requires a high level of detail and thus{{AbbrTemplate|IAMs}} such as [[TIMER model]] concentrate on introducing a set of simplified, meta relationships ([[Hoogwijk, 2004]]; [[Van Vuuren, 2007]]). <br /> <br /> <br /> ===Total demand for new capacity===<br /> The electricity capacity required to meet the demand per region is based on a forecast of the maximum electricity demand plus a reserve margin of about 10% (including the capacity credit assigned to different forms of electricity generation). Maximum demand is calculated on the basis of an assumed monthly shape of the load duration curve (LDC) and the gross electricity demand. The latter comprises the net electricity demand from the end-use sectors plus electricity trade and transmission losses (LDC accounts for characteristics such as cooling and lighting demand). The demand for new generation capacity is the difference between the required and existing capacity. Power plants are assumed to be replaced at the end of their lifetime, which varies from 30 to 50 years, depending on the technology and is currently fixed in the model.<br /> <br /> ===Decisions to invest in specific options ===<br /> In the following step, a decision is made to invest in different generation technologies. In the model, this is done on the basis of the price of electricity (in [[HasAcronym::USD/kWhe]]) produced per technology, using a multinomial logit equation that assigns larger market shares to the lower cost options. The specific costs of each option is broken down into a number of categories: investment or capital costs (USD/kWe), fuel costs ([[HasAcronym::USD/GJ]]), operational and maintenance costs (OM) and other costs (see further). An exception is hydropower capacity, which is exogenously prescribed, because large hydropower plants often have functions other than only electricity production (e.g. water supply and flood control). In the equations, some constraints are added to account for limitations in supply (e.g. restrictions on biomass availability). The investments needed for each option are given in the form of total investment in new generation capacity and the share of each individual technology (determined on the basis of price and preference).<br /> <br /> ==Operational strategy ==<br /> For the operational strategy, the use of power plants is based on operational costs: low-cost technologies are assumed to be used most often. This implies that capital-intensive plants with low operational costs, such as those for renewable and nuclear energy, in principle, will operate as many hours as possible. To some degree, this is also true for other plants with low operational costs (e.g. coal). Therefore, the operational decision is represented by the following three steps:<br /> #First, the renewable sources PV and wind are assigned, followed by hydropower, as these options have the lowest operational costs;<br /> #Second, the peak load capacity (i.e. period of high electricity demand) is assigned on the basis of operational costs of each available plant and the ability of these plants to provide such peak load capacity; <br /> #Third, base load (i.e. period of medium to low energy demand) is assigned on the basis of the remaining capacity (after steps 1 and 2), operational costs and the ability of options to provide the base load capacity.<br /> <br /> ==Fossil-fuel and bio-energy power plants==<br /> A total of 20 different types of power plants, generating electricity using fossil fuels and bio-energy, are included. These power plants represent different combinations of (i) conventional technology; (ii) gasification and combined cycle ([[HasAcronym::CC]]) technology; (iii) combined heat and power ([[HasAcronym::CHP]]) and, (iv) carbon capture and storage ([[HasAcronym::CCS]]) ([[Hendriks et al., 2004b]]). The specific capital costs and thermal efficiencies of these types of plants are determined by exogenous assumptions that describe the technological progress of typical components of these plants:<br /> *For conventional power plants, the coal-fired plant is defined in terms of overall efficiency and investment costs. The characteristics of all other conventional plants (using oil, natural gas or bio-energy) here are described in the investment differences for desulphurisation, fuel handling and efficiency.<br /> *For Combined Cycle (CC) power plants, the characteristics of a natural gas fuelled plant is set asthe standard. Other such plants (fuelled by oil, bio-energy and coal) are defined by indicating additional capital costs for gasification, efficiency losses due to gasification, and operation and maintenance ([[HasAcronym::O &amp; M]]) costs for fuel handling. <br /> *Power plants with carbon-capture-and-storage systems (CCS) are assumed to be CC plants, but with fuel-specific lower efficiency and higher investment and O&amp;M costs (related to capture and storage). <br /> *The characteristics of combined-heat-and-power plants (CHP) are similar to those of other plants, but with an assumed small increase in capital costs, in combination with a lower efficiency for electric conversion and an added factor for heat efficiency. <br /> <br /> The costs of one unit of electricity generated in these plants is equal to the sum of the capital costs, operation and maintenance costs (O&amp;M), fuel costs, and CO2 storage costs. <br /> <br /> ==Solar and wind power==<br /> <br /> {{FormulaAndTableTemplate|Formula1_ED}}<br /> <br /> The costs of solar and wind power are the model determined by learning and depletion dynamics. For renewable energy, costs relate to capital, O&amp;M and system integration. The capital costs mostly relate to [[Energy conversion/Description/Technical learning|learning]] and depletion processes (learning is represented by so-called learning curves; depletion is represented by long-term cost–supply curves). <br /> <br /> The additional system integration costs relate to <br /> # Discarded electricity in cases where production exceeds demand and the overcapacity cannot be used within the system;<br /> # Back-up capacity;<br /> # Additional required spinning reserve;<br /> The two last items are needed to avoid loss of power if the supply of wind or solar power suddenly drops, enabling a power scale up in a relatively short time, in power stations operating below maximum capacity ([[Hoogwijk, 2004]]).<br /> *To determine discarded electricity, the model makes a comparison between 10 different points on the load-demand curve, at the overlap between demand and supply. For both wind and solar power, a typical load–supply curve is assumed (see [[Hoogwijk, 2004]]). If supply exceeds demand, the overcapacity in electricity is assumed to be discarded, resulting in higher production costs. <br /> *Because wind and solar power supply is intermittent (i.e. it varies and therefore is not reliable), the model assumes that so-called back-up capacity needs to be installed. For the first 5% penetration of the intermittent capacity, it is assumed that no-back is required. However, for higher levels of penetration, the effective capacity (i.e. degree to which operators can rely on plants producing at a particular moment in time) of intermittent resources is assumed to decrease (referred to as the capacity factor). This decrease leads to the need of back-up power(by low-cost options, such as gas turbines), the costs of which are allocated to the intermittent source.<br /> *The required spinning reserve of the power system (capacity that can be used to respond to a rapid increase in demand) is assumed to be 3.5% of the installed capacity of a conventional power plant. If wind and solar power further penetrate the market, the model assumes an additional, required spinning reserve of 15% of the intermittent capacity (but after first subtracting the 3.5% existing capacity). The related costs are allocated to the intermittent source.<br /> <br /> ==Nuclear power==<br /> For nuclear power, the costs also consists of capital, O&amp;M and nuclear fuel costs. Similar to the renewable energy options, technology improvement nuclear power is described via a learning curve (so costs decrease with cumulative installed capacity). At the same time, fuel costs increase as a function of depletion. Fuel costs are determined on the basis of the estimated extraction costs of uranium and thorium resources, as is described in the component [[Energy supply]]. A small trade model for these fission fuels is included.<br /> <br /> ==Hydrogen generation model==<br /> The structure of the hydrogen model is similar to that of the electric power model ([[Van Ruijven et al., 2007]]). There are, however, some important differences:<br /> *The hydrogen model distinguishes the following 11 supply options: hydrogen production plants on the basis of coal, oil, natural gas and bio-energy, with and <br /> without carbon capture and storage (8 plants), hydrogen production from electrolysis, direct hydrogen production from solar thermal processes, and, finally, small methane reform plants. <br /> *For simplification, no description of preferences for different power plants is accounted for in the operational strategy. In other words, the load factor for each option equals the total production divided by the capacity for each region.<br /> *Intermittence does not play an important role, as hydrogen can be stored to some degree. Therefore, there are no equations simulating system integration.<br /> *Hydrogen can be traded. Therefore, a trade model is added, similar to the trade models for fossil fuels, as is described in the [[Energy supply]] section.<br /> <br /> &lt;references/&gt;<br /> }}</div>

JoeriOostenrijk https://models.pbl.nl/index.php?title=Energy_conversion/Description&diff=21482 2014-05-08T14:47:00Z

<p>JoeriOostenrijk: </p> <hr /> <div>{{ComponentDescriptionTemplate<br /> |Reference=Hoogwijk, 2004; Van Vuuren, 2007; Hendriks et al., 2004b; Van Ruijven et al., 2007;<br /> |Description=[[TIMER model]] includes two main energy conversion modules: Electric power generation and hydrogen generation. Below, electric power generation is described in detail. In addition, the key characteristics of the hydrogen generation model, which follows a similar structure, are presented.<br /> <br /> ==Electric power generation==<br /> <br /> As shown in the flowchart, two key elements of the electric power generation are the investment strategy and the operational strategy in the sector. A challenge in simulating electricity production in an aggregated model is that in reality electricity production depends on a range of complex factors, related to costs, reliance, and the time required to switch on technologies. Modelling these factors requires a high level of detail and thus{{AbbrTemplate|IAMs}} IAMs such as TIMER concentrate on introducing a set of simplified, meta relationships ([[Hoogwijk, 2004]]; [[Van Vuuren, 2007]]). <br /> <br /> <br /> ===Total demand for new capacity===<br /> The electricity capacity required to meet the demand per region is based on a forecast of the maximum electricity demand plus a reserve margin of about 10% (including the capacity credit assigned to different forms of electricity generation). Maximum demand is calculated on the basis of an assumed monthly shape of the load duration curve (LDC) and the gross electricity demand. The latter comprises the net electricity demand from the end-use sectors plus electricity trade and transmission losses (LDC accounts for characteristics such as cooling and lighting demand). The demand for new generation capacity is the difference between the required and existing capacity. Power plants are assumed to be replaced at the end of their lifetime, which varies from 30 to 50 years, depending on the technology and is currently fixed in the model.<br /> <br /> ===Decisions to invest in specific options ===<br /> In the following step, a decision is made to invest in different generation technologies. In the model, this is done on the basis of the price of electricity (in [[HasAcronym::USD/kWhe]]) produced per technology, using a multinomial logit equation that assigns larger market shares to the lower cost options. The specific costs of each option is broken down into a number of categories: investment or capital costs (USD/kWe), fuel costs ([[HasAcronym::USD/GJ]]), operational and maintenance costs (OM) and other costs (see further). An exception is hydropower capacity, which is exogenously prescribed, because large hydropower plants often have functions other than only electricity production (e.g. water supply and flood control). In the equations, some constraints are added to account for limitations in supply (e.g. restrictions on biomass availability). The investments needed for each option are given in the form of total investment in new generation capacity and the share of each individual technology (determined on the basis of price and preference).<br /> <br /> ==Operational strategy ==<br /> For the operational strategy, the use of power plants is based on operational costs: low-cost technologies are assumed to be used most often. This implies that capital-intensive plants with low operational costs, such as those for renewable and nuclear energy, in principle, will operate as many hours as possible. To some degree, this is also true for other plants with low operational costs (e.g. coal). Therefore, the operational decision is represented by the following three steps:<br /> #First, the renewable sources PV and wind are assigned, followed by hydropower, as these options have the lowest operational costs;<br /> #Second, the peak load capacity (i.e. period of high electricity demand) is assigned on the basis of operational costs of each available plant and the ability of these plants to provide such peak load capacity; <br /> #Third, base load (i.e. period of medium to low energy demand) is assigned on the basis of the remaining capacity (after steps 1 and 2), operational costs and the ability of options to provide the base load capacity.<br /> <br /> ==Fossil-fuel and bio-energy power plants==<br /> A total of 20 different types of power plants, generating electricity using fossil fuels and bio-energy, are included. These power plants represent different combinations of (i) conventional technology; (ii) gasification and combined cycle ([[HasAcronym::CC]]) technology; (iii) combined heat and power ([[HasAcronym::CHP]]) and, (iv) carbon capture and storage ([[HasAcronym::CCS]]) ([[Hendriks et al., 2004b]]). The specific capital costs and thermal efficiencies of these types of plants are determined by exogenous assumptions that describe the technological progress of typical components of these plants:<br /> *For conventional power plants, the coal-fired plant is defined in terms of overall efficiency and investment costs. The characteristics of all other conventional plants (using oil, natural gas or bio-energy) here are described in the investment differences for desulphurisation, fuel handling and efficiency.<br /> *For Combined Cycle (CC) power plants, the characteristics of a natural gas fuelled plant is set asthe standard. Other such plants (fuelled by oil, bio-energy and coal) are defined by indicating additional capital costs for gasification, efficiency losses due to gasification, and operation and maintenance ([[HasAcronym::O &amp; M]]) costs for fuel handling. <br /> *Power plants with carbon-capture-and-storage systems (CCS) are assumed to be CC plants, but with fuel-specific lower efficiency and higher investment and O&amp;M costs (related to capture and storage). <br /> *The characteristics of combined-heat-and-power plants (CHP) are similar to those of other plants, but with an assumed small increase in capital costs, in combination with a lower efficiency for electric conversion and an added factor for heat efficiency. <br /> <br /> The costs of one unit of electricity generated in these plants is equal to the sum of the capital costs, operation and maintenance costs (O&amp;M), fuel costs, and CO2 storage costs. <br /> <br /> ==Solar and wind power==<br /> <br /> {{FormulaAndTableTemplate|Formula1_ED}}<br /> <br /> The costs of solar and wind power are the model determined by learning and depletion dynamics. For renewable energy, costs relate to capital, O&amp;M and system integration. The capital costs mostly relate to [[Energy conversion/Description/Technical learning|learning]] and depletion processes (learning is represented by so-called learning curves; depletion is represented by long-term cost–supply curves). <br /> <br /> The additional system integration costs relate to <br /> # Discarded electricity in cases where production exceeds demand and the overcapacity cannot be used within the system;<br /> # Back-up capacity;<br /> # Additional required spinning reserve;<br /> The two last items are needed to avoid loss of power if the supply of wind or solar power suddenly drops, enabling a power scale up in a relatively short time, in power stations operating below maximum capacity ([[Hoogwijk, 2004]]).<br /> *To determine discarded electricity, the model makes a comparison between 10 different points on the load-demand curve, at the overlap between demand and supply. For both wind and solar power, a typical load–supply curve is assumed (see [[Hoogwijk, 2004]]). If supply exceeds demand, the overcapacity in electricity is assumed to be discarded, resulting in higher production costs. <br /> *Because wind and solar power supply is intermittent (i.e. it varies and therefore is not reliable), the model assumes that so-called back-up capacity needs to be installed. For the first 5% penetration of the intermittent capacity, it is assumed that no-back is required. However, for higher levels of penetration, the effective capacity (i.e. degree to which operators can rely on plants producing at a particular moment in time) of intermittent resources is assumed to decrease (referred to as the capacity factor). This decrease leads to the need of back-up power(by low-cost options, such as gas turbines), the costs of which are allocated to the intermittent source.<br /> *The required spinning reserve of the power system (capacity that can be used to respond to a rapid increase in demand) is assumed to be 3.5% of the installed capacity of a conventional power plant. If wind and solar power further penetrate the market, the model assumes an additional, required spinning reserve of 15% of the intermittent capacity (but after first subtracting the 3.5% existing capacity). The related costs are allocated to the intermittent source.<br /> <br /> ==Nuclear power==<br /> For nuclear power, the costs also consists of capital, O&amp;M and nuclear fuel costs. Similar to the renewable energy options, technology improvement nuclear power is described via a learning curve (so costs decrease with cumulative installed capacity). At the same time, fuel costs increase as a function of depletion. Fuel costs are determined on the basis of the estimated extraction costs of uranium and thorium resources, as is described in the component [[Energy supply]]. A small trade model for these fission fuels is included.<br /> <br /> ==Hydrogen generation model==<br /> The structure of the hydrogen model is similar to that of the electric power model ([[Van Ruijven et al., 2007]]). There are, however, some important differences:<br /> *The hydrogen model distinguishes the following 11 supply options: hydrogen production plants on the basis of coal, oil, natural gas and bio-energy, with and <br /> without carbon capture and storage (8 plants), hydrogen production from electrolysis, direct hydrogen production from solar thermal processes, and, finally, small methane reform plants. <br /> *For simplification, no description of preferences for different power plants is accounted for in the operational strategy. In other words, the load factor for each option equals the total production divided by the capacity for each region.<br /> *Intermittence does not play an important role, as hydrogen can be stored to some degree. Therefore, there are no equations simulating system integration.<br /> *Hydrogen can be traded. Therefore, a trade model is added, similar to the trade models for fossil fuels, as is described in the [[Energy supply]] section.<br /> <br /> &lt;references/&gt;<br /> }}</div>

JoeriOostenrijk https://models.pbl.nl/index.php?title=Energy_conversion/Description&diff=21481 2014-05-08T14:46:25Z

<p>JoeriOostenrijk: </p> <hr /> <div>{{ComponentDescriptionTemplate<br /> |Reference=Hoogwijk, 2004; Van Vuuren, 2007; Hendriks et al., 2004b; Van Ruijven et al., 2007;<br /> |Description=[[TIMER model]] includes two main energy conversion modules: Electric power generation and hydrogen generation. Below, electric power generation is described in detail. In addition, the key characteristics of the hydrogen generation model, which follows a similar structure, are presented.<br /> <br /> ==Electric power generation==<br /> <br /> As shown in the flowchart, two key elements of the electric power generation are the investment strategy and the operational strategy in the sector. A challenge in simulating electricity production in an aggregated model is that in reality electricity production depends on a range of complex factors, related to costs, reliance, and the time required to switch on technologies. Modelling these factors requires a high level of detail and thus{{AbbrTemplate|IAM}} IAMs such as TIMER concentrate on introducing a set of simplified, meta relationships ([[Hoogwijk, 2004]]; [[Van Vuuren, 2007]]). <br /> <br /> <br /> ===Total demand for new capacity===<br /> The electricity capacity required to meet the demand per region is based on a forecast of the maximum electricity demand plus a reserve margin of about 10% (including the capacity credit assigned to different forms of electricity generation). Maximum demand is calculated on the basis of an assumed monthly shape of the load duration curve (LDC) and the gross electricity demand. The latter comprises the net electricity demand from the end-use sectors plus electricity trade and transmission losses (LDC accounts for characteristics such as cooling and lighting demand). The demand for new generation capacity is the difference between the required and existing capacity. Power plants are assumed to be replaced at the end of their lifetime, which varies from 30 to 50 years, depending on the technology and is currently fixed in the model.<br /> <br /> ===Decisions to invest in specific options ===<br /> In the following step, a decision is made to invest in different generation technologies. In the model, this is done on the basis of the price of electricity (in [[HasAcronym::USD/kWhe]]) produced per technology, using a multinomial logit equation that assigns larger market shares to the lower cost options. The specific costs of each option is broken down into a number of categories: investment or capital costs (USD/kWe), fuel costs ([[HasAcronym::USD/GJ]]), operational and maintenance costs (OM) and other costs (see further). An exception is hydropower capacity, which is exogenously prescribed, because large hydropower plants often have functions other than only electricity production (e.g. water supply and flood control). In the equations, some constraints are added to account for limitations in supply (e.g. restrictions on biomass availability). The investments needed for each option are given in the form of total investment in new generation capacity and the share of each individual technology (determined on the basis of price and preference).<br /> <br /> ==Operational strategy ==<br /> For the operational strategy, the use of power plants is based on operational costs: low-cost technologies are assumed to be used most often. This implies that capital-intensive plants with low operational costs, such as those for renewable and nuclear energy, in principle, will operate as many hours as possible. To some degree, this is also true for other plants with low operational costs (e.g. coal). Therefore, the operational decision is represented by the following three steps:<br /> #First, the renewable sources PV and wind are assigned, followed by hydropower, as these options have the lowest operational costs;<br /> #Second, the peak load capacity (i.e. period of high electricity demand) is assigned on the basis of operational costs of each available plant and the ability of these plants to provide such peak load capacity; <br /> #Third, base load (i.e. period of medium to low energy demand) is assigned on the basis of the remaining capacity (after steps 1 and 2), operational costs and the ability of options to provide the base load capacity.<br /> <br /> ==Fossil-fuel and bio-energy power plants==<br /> A total of 20 different types of power plants, generating electricity using fossil fuels and bio-energy, are included. These power plants represent different combinations of (i) conventional technology; (ii) gasification and combined cycle ([[HasAcronym::CC]]) technology; (iii) combined heat and power ([[HasAcronym::CHP]]) and, (iv) carbon capture and storage ([[HasAcronym::CCS]]) ([[Hendriks et al., 2004b]]). The specific capital costs and thermal efficiencies of these types of plants are determined by exogenous assumptions that describe the technological progress of typical components of these plants:<br /> *For conventional power plants, the coal-fired plant is defined in terms of overall efficiency and investment costs. The characteristics of all other conventional plants (using oil, natural gas or bio-energy) here are described in the investment differences for desulphurisation, fuel handling and efficiency.<br /> *For Combined Cycle (CC) power plants, the characteristics of a natural gas fuelled plant is set asthe standard. Other such plants (fuelled by oil, bio-energy and coal) are defined by indicating additional capital costs for gasification, efficiency losses due to gasification, and operation and maintenance ([[HasAcronym::O &amp; M]]) costs for fuel handling. <br /> *Power plants with carbon-capture-and-storage systems (CCS) are assumed to be CC plants, but with fuel-specific lower efficiency and higher investment and O&amp;M costs (related to capture and storage). <br /> *The characteristics of combined-heat-and-power plants (CHP) are similar to those of other plants, but with an assumed small increase in capital costs, in combination with a lower efficiency for electric conversion and an added factor for heat efficiency. <br /> <br /> The costs of one unit of electricity generated in these plants is equal to the sum of the capital costs, operation and maintenance costs (O&amp;M), fuel costs, and CO2 storage costs. <br /> <br /> ==Solar and wind power==<br /> <br /> {{FormulaAndTableTemplate|Formula1_ED}}<br /> <br /> The costs of solar and wind power are the model determined by learning and depletion dynamics. For renewable energy, costs relate to capital, O&amp;M and system integration. The capital costs mostly relate to [[Energy conversion/Description/Technical learning|learning]] and depletion processes (learning is represented by so-called learning curves; depletion is represented by long-term cost–supply curves). <br /> <br /> The additional system integration costs relate to <br /> # Discarded electricity in cases where production exceeds demand and the overcapacity cannot be used within the system;<br /> # Back-up capacity;<br /> # Additional required spinning reserve;<br /> The two last items are needed to avoid loss of power if the supply of wind or solar power suddenly drops, enabling a power scale up in a relatively short time, in power stations operating below maximum capacity ([[Hoogwijk, 2004]]).<br /> *To determine discarded electricity, the model makes a comparison between 10 different points on the load-demand curve, at the overlap between demand and supply. For both wind and solar power, a typical load–supply curve is assumed (see [[Hoogwijk, 2004]]). If supply exceeds demand, the overcapacity in electricity is assumed to be discarded, resulting in higher production costs. <br /> *Because wind and solar power supply is intermittent (i.e. it varies and therefore is not reliable), the model assumes that so-called back-up capacity needs to be installed. For the first 5% penetration of the intermittent capacity, it is assumed that no-back is required. However, for higher levels of penetration, the effective capacity (i.e. degree to which operators can rely on plants producing at a particular moment in time) of intermittent resources is assumed to decrease (referred to as the capacity factor). This decrease leads to the need of back-up power(by low-cost options, such as gas turbines), the costs of which are allocated to the intermittent source.<br /> *The required spinning reserve of the power system (capacity that can be used to respond to a rapid increase in demand) is assumed to be 3.5% of the installed capacity of a conventional power plant. If wind and solar power further penetrate the market, the model assumes an additional, required spinning reserve of 15% of the intermittent capacity (but after first subtracting the 3.5% existing capacity). The related costs are allocated to the intermittent source.<br /> <br /> ==Nuclear power==<br /> For nuclear power, the costs also consists of capital, O&amp;M and nuclear fuel costs. Similar to the renewable energy options, technology improvement nuclear power is described via a learning curve (so costs decrease with cumulative installed capacity). At the same time, fuel costs increase as a function of depletion. Fuel costs are determined on the basis of the estimated extraction costs of uranium and thorium resources, as is described in the component [[Energy supply]]. A small trade model for these fission fuels is included.<br /> <br /> ==Hydrogen generation model==<br /> The structure of the hydrogen model is similar to that of the electric power model ([[Van Ruijven et al., 2007]]). There are, however, some important differences:<br /> *The hydrogen model distinguishes the following 11 supply options: hydrogen production plants on the basis of coal, oil, natural gas and bio-energy, with and <br /> without carbon capture and storage (8 plants), hydrogen production from electrolysis, direct hydrogen production from solar thermal processes, and, finally, small methane reform plants. <br /> *For simplification, no description of preferences for different power plants is accounted for in the operational strategy. In other words, the load factor for each option equals the total production divided by the capacity for each region.<br /> *Intermittence does not play an important role, as hydrogen can be stored to some degree. Therefore, there are no equations simulating system integration.<br /> *Hydrogen can be traded. Therefore, a trade model is added, similar to the trade models for fossil fuels, as is described in the [[Energy supply]] section.<br /> <br /> &lt;references/&gt;<br /> }}</div>

JoeriOostenrijk https://models.pbl.nl/index.php?title=Energy_conversion/Description&diff=21480 2014-05-08T14:41:58Z

<p>JoeriOostenrijk: </p> <hr /> <div>{{ComponentDescriptionTemplate<br /> |Reference=Hoogwijk, 2004; Van Vuuren, 2007; Hendriks et al., 2004b; Van Ruijven et al., 2007;<br /> |Description=[[TIMER model]] includes two main energy conversion modules: Electric power generation and hydrogen generation. Below, electric power generation is described in detail. In addition, the key characteristics of the hydrogen generation model, which follows a similar structure, are presented.<br /> <br /> ==Electric power generation==<br /> <br /> As shown in the flowchart, two key elements of the electric power generation are the investment strategy and the operational strategy in the sector. A challenge in simulating electricity production in an aggregated model is that in reality electricity production depends on a range of complex factors, related to costs, reliance, and the time required to switch on technologies. Modelling these factors requires a high level of detail and thus IAMs such as TIMER concentrate on introducing a set of simplified, meta relationships ([[Hoogwijk, 2004]]; [[Van Vuuren, 2007]]). <br /> <br /> <br /> <br /> Electric power generation<br /> As shown in Figure 4.1.2.1, two key elements of the electric power generation are the investment strategy and the operational strategy in the sector. A challenge in simulating electricity production in an aggregated model is that in reality electricity production depends on a range of complex factors, related to costs, reliance, and the time required to switch on technologies. Modelling these factors requires a high level of detail and thus IAMs such as TIMER concentrate on introducing a set of simplified, meta relationships (Hoogwijk, 2004; Van Vuuren, 2007). <br /> <br /> <br /> Electric power generation<br /> As shown in the flowdiagram, two key elements of the electric power generation model are the descriptions of the investment strategy and the operational strategy within the sector. A challenge of simulating electricity production in an aggregated model is that, in reality, electricity production depends on a whole range of complex factors, such as those related to costs, reliance, and the time it takes to switch on technologies. Modelling these factors requires a very high level of detail. Therefore, IAMs such as TIMER concentrate on introducing a set of simplified, meta relationships ([[Hoogwijk, 2004]]; [[Van Vuuren, 2007]]). <br /> <br /> ==Total demand for new capacity en nu een helee lange koptekst die er af loop==<br /> The required electricity capacity needed to meet the demand per region is based on a forecast of the maximum electricity demand plus a reserve margin of about 10%. The maximum demand is calculated on the basis of an assumed monthly shape of the load duration curve ([[HasAcronym::LDC]]) and the gross electricity demand. The latter comprises the net electricity demand (from the end-use sectors) plus electricity trade and transmission losses (the LDC accounts for characteristics such as cooling and lighting demand). The demand for new generation capacity equals the difference between the required and existing capacity. Here, power plants are assumed to be replaced at the end of their lifetime (depending on the technology, varying from 30 to 50 years, and currently fixed in the model).<br /> <br /> ==Decisions to invest in specific options ==<br /> In the following step, a decision is made to invest in different generation technologies. In the model, this is done on the basis of the price of electricity (in [[HasAcronym::USD/kWhe]]) produced per technology, using a multinomial logit equation that assigns larger market shares to the lower cost options. The specific costs of each option is broken down into a number of categories: investment or capital costs (USD/kWe), fuel costs ([[HasAcronym::USD/GJ]]), operational and maintenance costs (OM) and other costs (see further). An exception is hydropower capacity, which is exogenously prescribed, because large hydropower plants often have functions other than only electricity production (e.g. water supply and flood control). In the equations, some constraints are added to account for limitations in supply (e.g. restrictions on biomass availability). The investments needed for each option are given in the form of total investment in new generation capacity and the share of each individual technology (determined on the basis of price and preference).<br /> <br /> ==Operational strategy ==<br /> For the operational strategy, the use of power plants is based on operational costs: low-cost technologies are assumed to be used most often. This implies that capital-intensive plants with low operational costs, such as those for renewable and nuclear energy, in principle, will operate as many hours as possible. To some degree, this is also true for other plants with low operational costs (e.g. coal). Therefore, the operational decision is represented by the following three steps:<br /> #First, the renewable sources PV and wind are assigned, followed by hydropower, as these options have the lowest operational costs;<br /> #Second, the peak load capacity (i.e. period of high electricity demand) is assigned on the basis of operational costs of each available plant and the ability of these plants to provide such peak load capacity; <br /> #Third, base load (i.e. period of medium to low energy demand) is assigned on the basis of the remaining capacity (after steps 1 and 2), operational costs and the ability of options to provide the base load capacity.<br /> <br /> ==Fossil-fuel and bio-energy power plants==<br /> A total of 20 different types of power plants, generating electricity using fossil fuels and bio-energy, are included. These power plants represent different combinations of (i) conventional technology; (ii) gasification and combined cycle ([[HasAcronym::CC]]) technology; (iii) combined heat and power ([[HasAcronym::CHP]]) and, (iv) carbon capture and storage ([[HasAcronym::CCS]]) ([[Hendriks et al., 2004b]]). The specific capital costs and thermal efficiencies of these types of plants are determined by exogenous assumptions that describe the technological progress of typical components of these plants:<br /> *For conventional power plants, the coal-fired plant is defined in terms of overall efficiency and investment costs. The characteristics of all other conventional plants (using oil, natural gas or bio-energy) here are described in the investment differences for desulphurisation, fuel handling and efficiency.<br /> *For Combined Cycle (CC) power plants, the characteristics of a natural gas fuelled plant is set asthe standard. Other such plants (fuelled by oil, bio-energy and coal) are defined by indicating additional capital costs for gasification, efficiency losses due to gasification, and operation and maintenance ([[HasAcronym::O &amp; M]]) costs for fuel handling. <br /> *Power plants with carbon-capture-and-storage systems (CCS) are assumed to be CC plants, but with fuel-specific lower efficiency and higher investment and O&amp;M costs (related to capture and storage). <br /> *The characteristics of combined-heat-and-power plants (CHP) are similar to those of other plants, but with an assumed small increase in capital costs, in combination with a lower efficiency for electric conversion and an added factor for heat efficiency. <br /> <br /> The costs of one unit of electricity generated in these plants is equal to the sum of the capital costs, operation and maintenance costs (O&amp;M), fuel costs, and CO2 storage costs. <br /> <br /> ==Solar and wind power==<br /> <br /> {{FormulaAndTableTemplate|Formula1_ED}}<br /> <br /> The costs of solar and wind power are the model determined by learning and depletion dynamics. For renewable energy, costs relate to capital, O&amp;M and system integration. The capital costs mostly relate to [[Energy conversion/Description/Technical learning|learning]] and depletion processes (learning is represented by so-called learning curves; depletion is represented by long-term cost–supply curves). <br /> <br /> The additional system integration costs relate to <br /> # Discarded electricity in cases where production exceeds demand and the overcapacity cannot be used within the system;<br /> # Back-up capacity;<br /> # Additional required spinning reserve;<br /> The two last items are needed to avoid loss of power if the supply of wind or solar power suddenly drops, enabling a power scale up in a relatively short time, in power stations operating below maximum capacity ([[Hoogwijk, 2004]]).<br /> *To determine discarded electricity, the model makes a comparison between 10 different points on the load-demand curve, at the overlap between demand and supply. For both wind and solar power, a typical load–supply curve is assumed (see [[Hoogwijk, 2004]]). If supply exceeds demand, the overcapacity in electricity is assumed to be discarded, resulting in higher production costs. <br /> *Because wind and solar power supply is intermittent (i.e. it varies and therefore is not reliable), the model assumes that so-called back-up capacity needs to be installed. For the first 5% penetration of the intermittent capacity, it is assumed that no-back is required. However, for higher levels of penetration, the effective capacity (i.e. degree to which operators can rely on plants producing at a particular moment in time) of intermittent resources is assumed to decrease (referred to as the capacity factor). This decrease leads to the need of back-up power(by low-cost options, such as gas turbines), the costs of which are allocated to the intermittent source.<br /> *The required spinning reserve of the power system (capacity that can be used to respond to a rapid increase in demand) is assumed to be 3.5% of the installed capacity of a conventional power plant. If wind and solar power further penetrate the market, the model assumes an additional, required spinning reserve of 15% of the intermittent capacity (but after first subtracting the 3.5% existing capacity). The related costs are allocated to the intermittent source.<br /> <br /> ==Nuclear power==<br /> For nuclear power, the costs also consists of capital, O&amp;M and nuclear fuel costs. Similar to the renewable energy options, technology improvement nuclear power is described via a learning curve (so costs decrease with cumulative installed capacity). At the same time, fuel costs increase as a function of depletion. Fuel costs are determined on the basis of the estimated extraction costs of uranium and thorium resources, as is described in the component [[Energy supply]]. A small trade model for these fission fuels is included.<br /> <br /> ==Hydrogen generation model==<br /> The structure of the hydrogen model is similar to that of the electric power model ([[Van Ruijven et al., 2007]]). There are, however, some important differences:<br /> *The hydrogen model distinguishes the following 11 supply options: hydrogen production plants on the basis of coal, oil, natural gas and bio-energy, with and <br /> without carbon capture and storage (8 plants), hydrogen production from electrolysis, direct hydrogen production from solar thermal processes, and, finally, small methane reform plants. <br /> *For simplification, no description of preferences for different power plants is accounted for in the operational strategy. In other words, the load factor for each option equals the total production divided by the capacity for each region.<br /> *Intermittence does not play an important role, as hydrogen can be stored to some degree. Therefore, there are no equations simulating system integration.<br /> *Hydrogen can be traded. Therefore, a trade model is added, similar to the trade models for fossil fuels, as is described in the [[Energy supply]] section.<br /> <br /> &lt;references/&gt;<br /> }}</div>

JoeriOostenrijk https://models.pbl.nl/index.php?title=Energy_conversion&diff=21479 2014-05-08T14:38:01Z

<p>JoeriOostenrijk: </p> <hr /> <div>{{ComponentTemplate2<br /> |Application=ADVANCE-WP5 project;<br /> |IMAGEComponent=Energy supply and demand; Energy demand; Energy supply; Agricultural systems; Climate policy; Scenario drivers;<br /> |KeyReference=Hoogwijk et al., 2007; Hendriks et al., 2004a;<br /> |InputVar=Energy policy; Air pollution policy; Demand for electricity, heat and hydrogen; Primary energy price; Carbon storage price; Carbon price; Technology development of energy conversion;<br /> |Parameter=Initial technology cost; Rules on use of technology;<br /> |OutputVar=Electricity price; Demand for primary energy; CO2 stored; Energy and industry activity level;<br /> |Description=Energy from primary sources often has to be converted into secondary energy carriers that are more easily accessible for final consumption, for example the production of electricity and hydrogen, oil products from crude oil in refineries, and fuels from biomass. Studies on transitions to more sustainable energy systems also show the importance of these conversions for the future.<br /> <br /> The energy conversion module of TIMER simulates the choices of input energy carriers in two steps. In the first step, investment decisions are made on the future generation mix in terms of newly added capital. In the second step, the actual use of the capacity in place depends on a set of model rules that determine the purpose and how frequently the different types of power plants are used (baseload/peakload). The discussion focuses on the production of electricity and hydrogen. Other conversion processes have only be implemented in the model by simple multipliers, as they mostly convert energy from a single primary source to one secondary energy carrier. These processes are discussed in [[Energy supply|primary energy (sub)model]].<br /> |ComponentCode=EC<br /> |AggregatedComponent=Energy supply and demand<br /> |FrameworkElementType=pressure component<br /> }}</div>

JoeriOostenrijk https://models.pbl.nl/index.php?title=FAO&diff=21008 2014-05-05T15:38:38Z

<p>JoeriOostenrijk: </p> <hr /> <div>{{ResearchOrganisationTemplate<br /> |Description=Food and Agriculture Organisation<br /> |URL=http://www.fao.org<br /> }}</div>

JoeriOostenrijk https://models.pbl.nl/index.php?title=Livestock_systems/Policy_issues&diff=21003 2014-05-05T15:32:28Z

<p>JoeriOostenrijk: </p> <hr /> <div>{{ComponentPolicyIssueTemplate<br /> |Description=Between 1970 and 2010, global grass consumption increased by more than 40% (see figure below), while global grassland area only increased about 5% from 3134 to 3313 million hectares in the same period (see the figure in the policy intervention example section). The global area of pastoral grassland only shows slight and gradual changes. <br /> While extensive pastoral production systems have changed little, mixed and industrial systems have moved rapidly towards intensification. Most baseline scenarios indicate that a similar slow increase in grassland area is required over the coming decades as observed historically. Under the baseline scenario from the [[Roads from Rio+20 (2012) project |Rio+20]] study, these developments result in a small increase of 2% in global grassland area (see the figure in the policy intervention example section), but this will require considerable productivity increases in many parts of the world as discussed in [[Bouwman et al., 2005]].<br /> |Example=A larger proportion of livestock production in mixed systems will inherently increase overall feed conversion ratios of ruminants;<br /> *production parameters, such as milk production per animal, carcass weight and off-take rates, will have an effect on the feed conversion ratio, which in general will be lower in more productive animals;<br /> *feed conversion ratio of small ruminants, such as sheep and goats, will reduce demand for grass;<br /> *the proportion of grass in the feed for cattle, and sheep and goats will decrease with the use of feed crops;<br /> *more intensive grazing will require improved grassland management, including use of grass-clover mixes and fertilisers, and aligning the grazing season with grass production and rotations.<br /> <br /> All such interventions have been combined in the Global Technology (GT) scenario of the [[Roads from Rio+20 (2012) project |Rio+20]] study, resulting in more production in mixed systems (+10%), higher carcass weights (+10%), higher off-take rates (+10%), more efficient feed conversion by sheep and goats (+10%), more feed crops (15%) and higher grazing intensities (15%). This package leads to a considerable reduction in grassland area of about 15% compared to the baseline scenario for 2050 (see figure below), leaving more area for biodiversity recovery.<br /> }}</div>

JoeriOostenrijk https://models.pbl.nl/index.php?title=Livestock_systems/Policy_issues&diff=21002 2014-05-05T15:31:43Z

<p>JoeriOostenrijk: </p> <hr /> <div>{{ComponentPolicyIssueTemplate<br /> |Description=Between 1970 and 2010, global grass consumption increased by more than 40% (see figure below), while global grassland area only increased about 5% from 3134 to 3313 million hectares in the same period (see the figure in the policy intervention example section). The global area of pastoral grassland only shows slight and gradual changes. <br /> While extensive pastoral production systems have changed little, mixed and industrial systems have moved rapidly towards intensification. Most baseline scenarios indicate that a similar slow increase in grassland area is required over the coming decades as observed historically. Under the baseline scenario from the [[Roads from Rio+20 (2012) project |Rio+20]] study, these developments result in a small increase of 2% in global grassland area (Figure 4.2.4.3), but this will require considerable productivity increases in many parts of the world as discussed in [[Bouwman et al., 2005]].<br /> |Example=A larger proportion of livestock production in mixed systems will inherently increase overall feed conversion ratios of ruminants;<br /> *production parameters, such as milk production per animal, carcass weight and off-take rates, will have an effect on the feed conversion ratio, which in general will be lower in more productive animals;<br /> *feed conversion ratio of small ruminants, such as sheep and goats, will reduce demand for grass;<br /> *the proportion of grass in the feed for cattle, and sheep and goats will decrease with the use of feed crops;<br /> *more intensive grazing will require improved grassland management, including use of grass-clover mixes and fertilisers, and aligning the grazing season with grass production and rotations.<br /> <br /> All such interventions have been combined in the Global Technology (GT) scenario of the [[Roads from Rio+20 (2012) project |Rio+20]] study, resulting in more production in mixed systems (+10%), higher carcass weights (+10%), higher off-take rates (+10%), more efficient feed conversion by sheep and goats (+10%), more feed crops (15%) and higher grazing intensities (15%). This package leads to a considerable reduction in grassland area of about 15% compared to the baseline scenario for 2050 (see figure below), leaving more area for biodiversity recovery.<br /> }}</div>

JoeriOostenrijk https://models.pbl.nl/index.php?title=Livestock_systems/Policy_issues&diff=21001 2014-05-05T15:30:08Z

<p>JoeriOostenrijk: </p> <hr /> <div>{{ComponentPolicyIssueTemplate<br /> |Description=Between 1970 and 2010, global grass consumption increased by more than 40% (see figure below), while global grassland area only increased about 5% from 3134 to 3313 million hectares in the same period (see the figure in the policy intervention example section). The global area of pastoral grassland only shows slight and gradual changes. <br /> While extensive pastoral production systems have changed little, mixed and industrial systems have moved rapidly towards intensification. Most baseline scenarios indicate that a similar slow increase in grassland area is required over the coming decades as observed historically. Under the baseline scenario from the [[Roads from Rio+20 (2012) project |Rio+20]] study, these developments result in a small increase of 2% in global grassland area (Figure 4.2.4.3), but this will require considerable productivity increases in many parts of the world as discussed in [[Bouwman et al., (2005)]].<br /> |Example=A larger proportion of livestock production in mixed systems will inherently increase overall feed conversion ratios of ruminants;<br /> *production parameters, such as milk production per animal, carcass weight and off-take rates, will have an effect on the feed conversion ratio, which in general will be lower in more productive animals;<br /> *feed conversion ratio of small ruminants, such as sheep and goats, will reduce demand for grass;<br /> *the proportion of grass in the feed for cattle, and sheep and goats will decrease with the use of feed crops;<br /> *more intensive grazing will require improved grassland management, including use of grass-clover mixes and fertilisers, and aligning the grazing season with grass production and rotations.<br /> <br /> All such interventions have been combined in the Global Technology (GT) scenario of the [[Roads from Rio+20 (2012) project |Rio+20]] study, resulting in more production in mixed systems (+10%), higher carcass weights (+10%), higher off-take rates (+10%), more efficient feed conversion by sheep and goats (+10%), more feed crops (15%) and higher grazing intensities (15%). This package leads to a considerable reduction in grassland area of about 15% compared to the baseline scenario for 2050 (see figure below), leaving more area for biodiversity recovery.<br /> }}</div>

JoeriOostenrijk https://models.pbl.nl/index.php?title=Livestock_systems/Policy_issues&diff=21000 2014-05-05T15:28:58Z

<p>JoeriOostenrijk: </p> <hr /> <div>{{ComponentPolicyIssueTemplate<br /> |Description=Between 1970 and 2010, global grass consumption increased by more than 40% (see figure below), while global grassland area only increased about 5% from 3134 to 3313 million hectares in the same period (see the figure in the policy intervention example section). The global area of pastoral grassland only shows slight and gradual changes. <br /> While extensive pastoral production systems have changed little, mixed and industrial systems have moved rapidly towards intensification. Most baseline scenarios indicate that a similar slow increase in grassland area is required over the coming decades as observed historically. Under the baseline scenario from the [[Roads from Rio+20 (2012) project |Rio+20]] study, these developments result in a small increase of 2% in global grassland area (Figure 4.2.4.3), but this will require considerable productivity increases in many parts of the world as discussed in [[Bouwman et al., (2005)]].<br /> |Example=A larger proportion of livestock production in mixed systems will inherently increase overall feed conversion ratios of ruminants;<br /> *production parameters, such as milk production per animal, carcass weight and off-take rates, will have an effect on the feed conversion ratio, which in general will be lower in more productive animals;<br /> *feed conversion ratio of small ruminants, such as sheep and goats, will reduce demand for grass;<br /> *the proportion of grass in the feed for cattle, and sheep and goats will decrease with the use of feed crops;<br /> *more intensive grazing will require improved grassland management, including use of grass-clover mixes and fertilisers, and aligning the grazing season with grass production and rotations.<br /> <br /> All such interventions have been combined in the Global Technology (GT) scenario of the Rio+20 study, resulting in more production in mixed systems (+10%), higher carcass weights (+10%), higher off-take rates (+10%), more efficient feed conversion by sheep and goats (+10%), more feed crops (15%) and higher grazing intensities (15%). This package leads to a considerable reduction in grassland area of about 15% compared to the baseline scenario for 2050 (see figure below), leaving more area for biodiversity recovery.<br /> }}</div>

JoeriOostenrijk https://models.pbl.nl/index.php?title=Livestock_systems/Policy_issues&diff=20999 2014-05-05T15:28:33Z

<p>JoeriOostenrijk: </p> <hr /> <div>{{ComponentPolicyIssueTemplate<br /> |Description=Between 1970 and 2010, global grass consumption increased by more than 40% (see figure below), while global grassland area only increased about 5% from 3134 to 3313 million hectares in the same period (see the figure in the policy intervention example section). The global area of pastoral grassland only shows slight and gradual changes. <br /> While extensive pastoral production systems have changed little, mixed and industrial systems have moved rapidly towards intensification. Most baseline scenarios indicate that a similar slow increase in grassland area is required over the coming decades as observed historically. Under the baseline scenario from the [[Roads from Rio+20 (2012) project |Rio+20]] study, these developments result in a small increase of 2% in global grassland area (Figure 4.2.4.3), but this will require considerable productivity increases in many parts of the world as discussed in [[Bouwman et al. (2005]]. <br /> |Example=A larger proportion of livestock production in mixed systems will inherently increase overall feed conversion ratios of ruminants;<br /> *production parameters, such as milk production per animal, carcass weight and off-take rates, will have an effect on the feed conversion ratio, which in general will be lower in more productive animals;<br /> *feed conversion ratio of small ruminants, such as sheep and goats, will reduce demand for grass;<br /> *the proportion of grass in the feed for cattle, and sheep and goats will decrease with the use of feed crops;<br /> *more intensive grazing will require improved grassland management, including use of grass-clover mixes and fertilisers, and aligning the grazing season with grass production and rotations.<br /> <br /> All such interventions have been combined in the Global Technology (GT) scenario of the Rio+20 study, resulting in more production in mixed systems (+10%), higher carcass weights (+10%), higher off-take rates (+10%), more efficient feed conversion by sheep and goats (+10%), more feed crops (15%) and higher grazing intensities (15%). This package leads to a considerable reduction in grassland area of about 15% compared to the baseline scenario for 2050 (see figure below), leaving more area for biodiversity recovery.<br /> <br /> }}</div>

JoeriOostenrijk https://models.pbl.nl/index.php?title=Livestock_systems/Policy_issues&diff=20998 2014-05-05T15:17:56Z

<p>JoeriOostenrijk: </p> <hr /> <div>{{ComponentPolicyIssueTemplate<br /> |Description=Between 1970 and 2010, global grass consumption increased by more than 40% (see figure below), while global grassland area only increased about 5% from 3134 to 3313 million hectares in the same period (Figure 4.2.4.3). The global area of pastoral grassland only shows slight and gradual changes. <br /> While extensive pastoral production systems have changed little, mixed and industrial systems have moved rapidly towards intensification. Most baseline scenarios indicate that a similar slow increase in grassland area is required over the coming decades as observed historically. Under the baseline scenario from the Rio+20 study, these developments result in a small increase of 2% in global grassland area (Figure 4.2.4.3), but this will require considerable productivity increases in many parts of the world as discussed in Bouwman et al. (2005). <br /> Baseline developments: Global grass consumption increased by more than 40% between 1970 and 2010 (see figure below), while global grassland area only increased about 5% from 3134 to 3313 million hectares in the same period (see the figure in the policy intervention example section). The global area of extensively used pastoral grassland only shows slight and gradual changes. <br /> While extensive pastoral production systems have changed little, mixed and industrial systems have moved rapidly towards intensification. Most baseline scenarios indicate a similar increase in grass production is required over the coming decades to that observed historically. Under the baseline scenario from the [[Roads from Rio+20 (2012) project |Rio+20]] study, these developments result in a small increase of 2% in global grassland area (see figure below). This smaller increase than observed historically is attributed to slower growth in consumption.<br /> |Example=All such interventions have been combined in the Global Technology (GT) scenario of the Rio+20 study, resulting in more production in mixed systems (+10%), higher carcass weights (+10%), higher off-take rates (+10%), more efficient feed conversion by sheep and goats (+10%), more feed crops (15%) and higher grazing intensities (15%). This package leads to a considerable reduction in grassland area of about 15% compared to the baseline scenario for 2050 (see the figure in the baseline scenario section), leaving more area for biodiversity recovery.<br /> }}</div>

JoeriOostenrijk https://models.pbl.nl/index.php?title=Livestock_systems/Description&diff=20997 2014-05-05T15:11:28Z

<p>JoeriOostenrijk: </p> <hr /> <div>{{ComponentDescriptionTemplate<br /> |Reference=Seré and Steinfeld, 1996;<br /> |Description===Livestock production==<br /> IMAGE distinguishes two livestock production systems, namely pastoral systems, and mixed and industrial systems, based on FAO ([[Seré and Steinfeld, 1996]]). Pastoral systems are mostly dominated by extensive ruminant production, while mixed and industrial systems are more intensive with animal husbandry comprising grazing ruminants and monogastrics. The distribution of livestock production in the two systems is constructed from historical data for the years up to the present, and for future years will depend on the scenario selected.<br /> <br /> ==Livestock==<br /> IMAGE distinguishes five types of livestock: beef, dairy cattle (large ruminants), the category sheep &amp; goats (small ruminants), pigs, and poultry (monogastrics). The numbers of animals and the proportion per production system are calculated from data on domestic livestock production per region provided by the agro-economic model MAGNET ([[Agricultural economy and forestry]]). The number of animals in each of the five livestock types is calculated from the total production per region and the characteristics of the livestock systems in that region. <br /> Stocks of dairy cows (POP) per country and world region are obtained from total milk production (PROD) and milk production per animal (MPH){{FormulaAndTableTemplate|Formula1_LS}}Animal stocks per region of beef cattle, pigs, and sheep and goats are obtained from production and carcass weight (CW) and off-take rate (OR):{{FormulaAndTableTemplate|Formula2_LS}}Historical data on milk production per cow, off-take rate, and carcass weight are obtained from statistics, and values for future years will depend on the scenario selected.<br /> <br /> ==Energy requirements==<br /> For dairy cattle, the energy requirements are calculated for maintenance (based on body weight), feeding (based on the proportion of grass in feed rations), lactation (based on milk production per cow) and pregnancy (based on the number of calves per year). The amount of feed dry matter is calculated on the basis of the proportion of digestible energy in the total energy intake, and the energy content of biomass.<br /> <br /> Energy requirements for cattle are based on animal activity and production, and for pigs, poultry, sheep and goats on Feed Conversion Ratios (FCR). This is the amount of feed (kg dry matter) required to produce one kilogram of milk or meat. The {{AbbrTemplate|FCR}} values are based on historical data and values for future years will depend on the scenario selected.<br /> <br /> ==Cropland and grassland required==<br /> Areas for feed crop production and grass are calculated on the basis of feed crop and grass requirements ([[Agricultural systems]]), which are calculated from total feed requirement and diet composition (feed rations, see below). <br /> Composition of animal feed<br /> IMAGE distinguishes five feed categories: <br /> #grass, including hay and grass silage; <br /> #food crops and processing by-products; <br /> #crop residues in the field after harvesting, and fodder crops; <br /> #animal products; <br /> #foraging including roadside grazing, scavenging household waste, and feedstuffs from backyard farming.<br /> <br /> In pastoral ruminant production systems, the feed is almost entirely grass except in developing regions where foraging constitutes a larger but variable proportion of the total feed. Pigs and poultry are fed feed crops and by-products, crop residues and fodder. Since these animals are mainly farmed in mixed systems, the contribution of feed crops and residues to the total feed in these systems is much higher than in pastoral systems.<br /> <br /> The required feed crop production per animal is calculated from feed rations, and this information is incorporated into the agro-economic model ([[Agricultural economy and forestry]]). The proportion of grass in feed rations determines total grass consumption, which is used to compute the grassland area per world region, based on grazing intensity ([[Agricultural economy and forestry]] and [[Agricultural systems]]).<br /> <br /> ==Scenario definition==<br /> A scenario includes assumptions on milk production per animal for dairy cattle, carcass weight and off-take rate for beef cattle, pigs, poultry, sheep and goats, and feed conversion rates (FCR) for pigs, poultry, sheep and goats. The changes in these parameters are generally based on the scenario, and on the economic growth scenario.<br /> }}</div>

JoeriOostenrijk