Technological change in energy - REMIND-MAgPIE: Difference between revisions
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REMIND assumes endogenous technological change through learning-by-doing for wind and solar power, electric (BEV) and fuel cell vehicle (FCV) technologies, as well as variable renewable energy (VRE) storage, through global learning curves and internalized spillovers. The specific investment costs for wind, solar PV, and solar CSP decrease by 12, 20, and 9%, respectively, for each doubling of cumulated capacity. The capital costs of the generalized storage units for VRE as well as of advanced vehicle technologies (BEV, FCV) decrease with a 10% learning rate. REMIND reduces learning rates as capacities increase such that the investment costs asymptotically approach exogenously prescribed floor costs (cf. | REMIND assumes endogenous technological change through learning-by-doing for wind and solar power, electric (BEV) and fuel cell vehicle (FCV) technologies, as well as variable renewable energy (VRE) storage, through global learning curves and internalized spillovers. The specific investment costs for wind, solar PV, and solar CSP decrease by 12, 20, and 9%, respectively, for each doubling of cumulated capacity. The capital costs of the generalized storage units for VRE as well as of advanced vehicle technologies (BEV, FCV) decrease with a 10% learning rate. REMIND reduces learning rates as capacities increase such that the investment costs asymptotically approach exogenously prescribed floor costs (cf. Table 6 and Table 8). | ||
As discussed in Section Final Energy Demand, REMIND represents energy efficiency improvements via an exogenously prescribed increase in the efficiency parameters of the CES production function, as well as price induced reductions in energy demand and changes in technology choice. | |||
As discussed in Section | REMIND represents investment dynamics in terms of capital motion equations, vintages for energy supply technologies and adjustment costs related to the acceleration of capacity expansion (for further details see Section Energy Conversion). | ||
REMIND represents investment dynamics in terms of capital motion equations, vintages for energy supply technologies and adjustment costs related to the acceleration of capacity expansion (for further details see Section | |||
Revision as of 20:35, 19 October 2016
| 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 | |
REMIND assumes endogenous technological change through learning-by-doing for wind and solar power, electric (BEV) and fuel cell vehicle (FCV) technologies, as well as variable renewable energy (VRE) storage, through global learning curves and internalized spillovers. The specific investment costs for wind, solar PV, and solar CSP decrease by 12, 20, and 9%, respectively, for each doubling of cumulated capacity. The capital costs of the generalized storage units for VRE as well as of advanced vehicle technologies (BEV, FCV) decrease with a 10% learning rate. REMIND reduces learning rates as capacities increase such that the investment costs asymptotically approach exogenously prescribed floor costs (cf. Table 6 and Table 8). As discussed in Section Final Energy Demand, REMIND represents energy efficiency improvements via an exogenously prescribed increase in the efficiency parameters of the CES production function, as well as price induced reductions in energy demand and changes in technology choice. REMIND represents investment dynamics in terms of capital motion equations, vintages for energy supply technologies and adjustment costs related to the acceleration of capacity expansion (for further details see Section Energy Conversion).