Energy demand/Description: Difference between revisions
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Here, IMS is the indicated market share of different energy carriers (or technologies) and c is their ‘costs’. In this equation, λ represents the so-called logit parameter, determining the sensitivity of markets to price differences. In the equation, not only direct production costs are accounted for, but also energy and carbon taxes and so-called premium values. The last reflect non-price factors determining market shares, such as preferences, environmental policies, infrastructures (or the lack thereof) and strategic considerations. These premium values are determined in the model’s calibration process in order to simulate correctly historical market shares on the basis of simulated price information. The same parameters are used in scenarios as a way of simulating the assumption of societal preferences for clean and/or convenient fuels. The market shares of traditional biomass and secondary heat, in contrast, are determined by exogenous scenario parameters (except for the residential sector discussed below). | Here, IMS is the indicated market share of different energy carriers (or technologies) and c is their ‘costs’. In this equation, λ represents the so-called logit parameter, determining the sensitivity of markets to price differences. In the equation, not only direct production costs are accounted for, but also energy and carbon taxes and so-called premium values. The last reflect non-price factors determining market shares, such as preferences, environmental policies, infrastructures (or the lack thereof) and strategic considerations. These premium values are determined in the model’s calibration process in order to simulate correctly historical market shares on the basis of simulated price information. The same parameters are used in scenarios as a way of simulating the assumption of societal preferences for clean and/or convenient fuels. The market shares of traditional biomass and secondary heat, in contrast, are determined by exogenous scenario parameters (except for the residential sector discussed below). | ||
Non-energy use of energy carriers is modelled on the basis of exogenously assumed intensity of representative non-energy uses (chemicals) and on a price-driven competition between the various energy carriers | Non-energy use of energy carriers is modelled on the basis of exogenously assumed intensity of representative non-energy uses (chemicals) and on a price-driven competition between the various energy carriers ([[Daioglou et al. (unpublished)]]). | ||
==Heavy industry submodel== | ==Heavy industry submodel== | ||
The heavy industry submodel was implemented for the steel and cement sector ([[Van Ruijven et al., 2013]]). These two sectors represented about 8% of global energy use and 13% of global anthropogenic greenhouse gas emissions in 2005. The generic structure of the energy demand model was adapted in several ways: | The heavy industry submodel was implemented for the steel and cement sector ([[Van Ruijven et al., 2013]]). These two sectors represented about 8% of global energy use and 13% of global anthropogenic greenhouse gas emissions in 2005. The generic structure of the energy demand model was adapted in several ways: | ||