Electricity - REMIND

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Model Documentation - REMIND

Corresponding documentation
Previous versions
Model information
Model link
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).

Table 1: Energy Conversion Technologies for Electricity
Energy Carrier Technology
Primary exhaustible resource
  • Conventional coal power plant
  • Integrated coal gasification combined cycle†
  • Coal combined heat and power plant
  • Diesel oil turbine
  • Gas turbine
  • Natural gas combined cycle†
  • Gas combined heat and power plant
  • Light water reactor
Primary renewable resource
  • Solar photovoltaic
  • Concentrating solar power
  • Wind turbine
  • Hydropower
  • Integrated biomass gasification combined cycle†
  • Biomass combined heat and power plant
  • Hot dry rock
Secondary energy type
  • Hydrogen turbine

Table 2. Techno-economic characteristics of technologies based on exhaustible energy sources and biomass [1]; [2]; [3]; [4]; [5]; [6]; [7]; [8]; [9]; [10]; [11]; [12]; [13].

Remind Table 5.PNG

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 [14].

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.

Table 3. Techno-economic characteristics of technologies based on non-biomass renewable energy sources [15]; [16]; [17]; [18]; [19].

Remind Table 6.PNG

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  13. Chen C, Rubin ES (2009) CO2 control technology effects on IGCC plant performance and cost. Energy Policy 37:915–924. doi: 10.1016/j.enpol.2008.09.093
  14. Sullivan P, Krey V, Riahi K (2013) Impacts of considering electric sector variability and reliability in the MESSAGE model. Energy Strategy Reviews 1:157–163. doi: 10.1016/j.esr.2013.01.001
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