Electricity - REMIND
|Institution||Potsdam Institut für Klimafolgenforschung (PIK), Germany, https://www.pik-potsdam.de/research/sustainable-solutions/models/remind.|
|Solution concept||General equilibrium (closed economy)MAgPIE: partial equilibrium model of the agricultural sector;|
|Solution method||OptimizationMAgPIE: cost minimization;|
Around twenty electricity generation technologies are represented in REMIND, see Table 1, with several low-carbon (CCS) and zero carbon options (nuclear and renewables).
Table 1. Energy Conversion Technologies for Electricity (Note: † indicates that technologies can be combined with CCS).
|Primary exhaustible resource|
|Primary renewable resource|
|Secondary energy type|
Abbreviations: PC - pulverized coal, IGCC - integrated coal gasification combined cycle, CHP - coal combined heat and power plant, C2H2 - coal to hydrogen, C2L - coal to liquids, C2G - coal gasification, NGT - natural gas turbine, NGCC - natural gas combined cycle, SMR - steam methane reforming, BIGCC – Biomass IGCC, BioCHP – biomass combined heat and power, B2H2 – biomass to hydrogen, B2L – biomass to liquids, B2G – biogas, TNR - thermo-nuclear reactor; * for joint production processes; § nuclear reactors with thermal efficiency of 33%; # technologies with exogenously improving efficiencies. 2005 values are represented by the lower end of the range. Long-term efficiencies (reached after 2045) are represented by high-end ranges.
For variable renewable energies, we implemented two parameterized cost markup functions for storage and long-distance transmission grids - see Section Grid and Infrastructure. To represent the general need for flexibility even in a thermal power system, we included a further flexibility constraint based on Sullivan .
The techno-economic parameters of power technologies used in the model are given in Table 2 for fuel-based technologies and Table 3 for non-biomass renewables. For wind, solar and hydro, capacity factors depend on grades, see Section Non-biomass renewables.
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