Electricity - REMIND-MAgPIE

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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

Around twenty electricity generation technologies are represented in REMIND, see Table 4, with several low-carbon (CCS) and zero carbon options (nuclear and renewables).

Table 4. Energy Conversion Technologies for Electricity (Note: * indicates that technologies can be combined with CCS).

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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 et al. (2013).

The techno-economic parameters of power technologies used in the model are given in Table 5 for fuel-based technologies and Table 6 for non-biomass renewables. For wind, solar and hydro, capacity factors depend on grades, see Section Non-biomass renewables.

Table 5. Techno-economic characteristics of technologies based on exhaustible energy sources and biomass (Iwasaki 2003; Hamelinck 2004; Bauer 2005; Ansolabehere et al. 2007; Gül et al. 2007; Ragettli 2007; Schulz 2007; Uddin and Barreto 2007; Rubin et al. 2007; Takeshita and Yamaji 2008; Brown et al. 2009; Klimantos et al. 2009; Chen and Rubin 2009).

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For abbreviations see Table Acronyms and Abbreviations ; * 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.

Table 6. Techno-economic characteristics of technologies based on non-biomass renewable energy sources (Neij et al. 2003; Nitsch et al. 2004; IEA 2007a; Junginger et al. 2008; Pietzcker et al. 2014).

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