Energy demand/Description: Difference between revisions
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==Residential submodel== | ==Residential submodel== | ||
The residential submodel describes the energy demand from several household energy functions, which described in detail in [[Daioglou et al., 2012]] and [[Van Ruijven et al., 2011]]. The residential model focuses on the five most important end-use functions: cooking, appliances, space heating and cooling, water heating and lighting. | The residential submodel describes the energy demand from several household energy functions, which described in detail in [[Daioglou et al., 2012]] and [[Van Ruijven et al., 2011]]. The residential model focuses on the five most important end-use functions: cooking, appliances, space heating and cooling, water heating and lighting. | ||
*Structural change in energy demand is presented through the modelling of end-use functions on household level. Energy service demand for space heating is modelled using correlations with floor area, heating degree days and energy intensity, the last including building efficiency improvements. Hot water demand is modelled as a function of household income and heating degree days. Energy service demand for cooking is determined on the basis of an average constant consumption of 3 MJUE/capita/day. Energy use related to appliances is based on ownership, household income, efficiency reference values, and autonomous and price-induced improvements. Space cooling follows a similar approach, but also includes cooling degree days ([[Isaac and | *Structural change in energy demand is presented through the modelling of end-use functions on household level. Energy service demand for space heating is modelled using correlations with floor area, heating degree days and energy intensity, the last including building efficiency improvements. Hot water demand is modelled as a function of household income and heating degree days. Energy service demand for cooking is determined on the basis of an average constant consumption of 3 MJUE/capita/day. Energy use related to appliances is based on ownership, household income, efficiency reference values, and autonomous and price-induced improvements. Space cooling follows a similar approach, but also includes cooling degree days ([[Isaac and van Vuuren, 2009]]). Finally, electricity use for lighting is determined on the basis of floor area, wattage and lighting hours (based on geographic location). | ||
*Efficiency improvements are included in different ways. For appliances, light bulbs, air conditioning, building insulation and heating equipment, the model uses an exogenously driven energy efficiency improvement over time. Price-induced energy efficiency improvements (PIEEI) occur by explicitly describing the investments in appliances with a similar performance level but with different energy and investment costs (e.g. the competition between incandescent light bulbs and more energy-efficient lighting is determined by changes in energy prices). | *Efficiency improvements are included in different ways. For appliances, light bulbs, air conditioning, building insulation and heating equipment, the model uses an exogenously driven energy efficiency improvement over time. Price-induced energy efficiency improvements (PIEEI) occur by explicitly describing the investments in appliances with a similar performance level but with different energy and investment costs (e.g. the competition between incandescent light bulbs and more energy-efficient lighting is determined by changes in energy prices). | ||
*The model distinguishes five income quintiles for both the urban and the rural population. After determining the energy demand per function for each population quintile, the choice of fuel type is determined on the basis of relative costs. This is, again, based on a multinomial logit formulation for energy functions that can involve multiple fuels, such as cooking and space heating. For developing countries, the model also uses a simulation of the so-called energy ladder (the process of using more modern energy types along with income growth, starting from traditional bio-energy via coal, kerosene to energy carriers such as natural gas, heating oil and electricity) through decreasing discount rates applied by consumers and increasing appreciation of clean and convenient fuels as a function of household income levels ([[Van Ruijven et al., 2011]]). | *The model distinguishes five income quintiles for both the urban and the rural population. After determining the energy demand per function for each population quintile, the choice of fuel type is determined on the basis of relative costs. This is, again, based on a multinomial logit formulation for energy functions that can involve multiple fuels, such as cooking and space heating. For developing countries, the model also uses a simulation of the so-called energy ladder (the process of using more modern energy types along with income growth, starting from traditional bio-energy via coal, kerosene to energy carriers such as natural gas, heating oil and electricity) through decreasing discount rates applied by consumers and increasing appreciation of clean and convenient fuels as a function of household income levels ([[Van Ruijven et al., 2011]]). | ||