Residential and commercial sectors - REMIND-MAgPIE: Difference between revisions

From IAMC-Documentation
Jump to navigation Jump to search
No edit summary
m (Text replacement - "REMIND" to "REMIND-MAgPIE")
 
(One intermediate revision by one other user not shown)
Line 1: Line 1:
{{ModelDocumentationTemplate
{{ModelDocumentationTemplate
|IsEmpty=No
|IsEmpty=No
|IsDocumentationOf=REMIND
|IsDocumentationOf=REMIND-MAgPIE
|DocumentationCategory=Residential and commercial sectors
|DocumentationCategory=Residential and commercial sectors
}}
}}
In REMIND, the residential and commercial sectors are modeled together within the buildings sector. The demand and the supply of energy for buildings follow different modelling approaches:
In REMIND-MAgPIE, the residential and commercial sectors are modeled together within the buildings sector. The demand and the supply of energy for buildings follow different modelling approaches:


'''Demand''' for energy types used in the buildings sector (electricity, solids, liquids, gas, district heat, and hydrogen) is modeled in a top-down fashion: they are input to a nested CES production function that produces GDP.   
'''Demand''' for energy types used in the buildings sector (electricity, solids, liquids, gas, district heat, and hydrogen) is modeled in a top-down fashion: they are input to a nested CES production function that produces GDP.   

Latest revision as of 14:35, 21 November 2021

Model Documentation - REMIND-MAgPIE

Corresponding documentation
Previous versions
Model information
Model link
Institution Potsdam Institut für Klimafolgenforschung (PIK), Germany, https://www.pik-potsdam.de.
Solution concept General equilibrium (closed economy)MAgPIE: partial equilibrium model of the agricultural sector;
Solution method OptimizationMAgPIE: cost minimization;
Anticipation

In REMIND-MAgPIE, the residential and commercial sectors are modeled together within the buildings sector. The demand and the supply of energy for buildings follow different modelling approaches:

Demand for energy types used in the buildings sector (electricity, solids, liquids, gas, district heat, and hydrogen) is modeled in a top-down fashion: they are input to a nested CES production function that produces GDP.

Supply of these final energies is modeled in a bottom-up energy model, where detailed capital stocks of conversion technologies convert primary energies to secondary and final energies, with full substitutability between technologies. The bottom-up energy model is described in full detail in Section “Energy conversion”.

The buildings sector differentiates between two explicit energy functions: electricity, and all energy inputs used for heating purposes (gas, solids, district heat, liquids, and hydrogen). It is easier to substitute one energy carrier for another in the latter group, than it is to substitute electricity for another energy carrier (see Figure 3 for the full CES production function with all substitution elasticity values).

The main energy demand drivers are GDP growth, the autonomous efficiency improvements (efficiency parameters of CES production function), the elasticities of substitution between capital and energy and between the buildings, industry, and transport energy sectors. These drivers influence demand in a similar manner as described for the transport sector, i.e. final energy types are inputs to a CES function, the output of which is combined with transport energy in another CES function to generate a generalized energy good, which in turn is combined with labor and capital in the main production function for GDP.

The indirect energy use and material needs for production of appliances or houses is not explicitly represented, only implicitly accounted for by the main CES production function, which is calibrated to the total historical energy demand of a region.

Inside a model run, different FE prices (due to climate policy, different resource assumptions, etc.) can lead to substitution of different buildings energy types inside the CES function, or a total reduction of buildings energy demand. There is no single direct price elasticity of demand in the model, the nested CES function results in different price elasticities at different points in time/system configurations. The buildings sector generates direct emissions – from fuel combustion in buildings and is responsible for indirect emissions (emissions from the energy supply sector) that go into the climate model and, depending on the scenario, are taxed or limited by a budget.