Energy demand - REMIND-MAgPIE
| Corresponding documentation | |
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| 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 | |
Economic activity results in demand for final energy determined by the macro-economic production function. REMIND distinguishes between the stationary end-use sector (aggregating industry and residential & commercial) and the transport end-use sector. The distribution of energy carriers to end-use sectors forms the interface between the macro-economic module and the energy system module. Table 2 maps secondary energy supply to end-use sectors. REMIND represents transport and distribution of secondary energy carriers in terms of capacities that require investments and incur costs for operation and maintenance. These costs shift the final energy supply curves and depend on the mode of transportation. The effect for electricity is larger than for liquid fuels.
In REMIND, there are three mechanisms for reductions in energy intensity, i.e. a decline in the use of energy for energy service input per unit of economic output. First, the efficiency parameters of the production function (exogenous) lead to autonomous reductions in energy intensity, which also occur in the absence of climate policy interventions. For 2005, the parameters are calibrated based on IEA energy balance sheets (IEA 2007a; IEA 2007b). We assume energy-related CES-efficiency parameters to change at the same rate as labor efficiency, including an additional adjustment factor. The model calibrates this factor separately for each region and each final energy type, so as to induce a gradual shift from solids and liquids to gases, transportation fuels and electricity, reflecting patterns of modernization observed in the past. We derive the reference trajectories for baseline scenarios without climate policy based on the following guidelines:
- Short- and mid-term final energy demand follows the trend for the years 2000-2010, which is consistent with most of the regional projections shown in the ?current policy scenario? of IEA WEO 2010.
- Per-capita energy use for the end-use of transport, non-electric stationary, and stationary electricity follow a converging trend between regions (EJ/capita over GDP in PPP/cap).
Second, the CES production function allows for price dependent substitutions between aggregated energy and capital (substitution elasticity of 0.5). The introduction of additional constraints on the supply side (e.g., carbon taxes, resource, or emission constraints) results in higher energy prices and thus lower final energy consumption compared to the reference trajectories. As a consequence, the share of macro-economic capital input to the production function increases. In absence of distortions, a reduction in final energy results in a lower GDP and, subsequently, lower consumption and welfare vaThird, the model can endogenously improve end-use efficiency by investing in more efficient technologies for the conversion of final energies into energy services. For example, three vehicle technologies with different efficiencies are implemented in the light duty vehicle (LDV) mode of the transport sector, including internal combustion engine vehicles, battery-electric vehicles, and fuel cell vehicles.
Table 2 - Overview of energy carriers used in end-use sectors.
| Sector | Electricity | Gases | Liquids | Hydrogen | Solids | Heat |
| Stationary | x | x | x | x | x | x |
| Transport | x | - | x | x | - | - |
Behavioural change
Prices are determined via price response through the CES production function.
There is no explicit modeling of behavioral change. However, baseline energy demands are calibrated in such a way that the energy demand patterns in different regions slowly converge when displayed as per capita energy demand over per capita GDP.