Electricity - REMIND-MAgPIE: Difference between revisions
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'' * for ''joint production processes;'' '''<sup>§</sup>''' ''nuclear reactors with thermal efficiency of 33%; <sup>#</sup> 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 ''joint production processes;'' '''<sup>§</sup>''' ''nuclear reactors with thermal efficiency of 33%; <sup>#</sup> 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 et al. (2013). | 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 <ref>Sullivan et al. (2013)</ref>. | ||
The techno-economic parameters of power technologies used in the model are given in <xr id="tab:REMINDtable_5"/> for fuel-based technologies and <xr id="tab:REMINDtable_6"/> for non-biomass renewables. For wind, solar and hydro, capacity factors depend on grades, see Section Non-biomass renewables. | The techno-economic parameters of power technologies used in the model are given in <xr id="tab:REMINDtable_5"/> for fuel-based technologies and <xr id="tab:REMINDtable_6"/> for non-biomass renewables. For wind, solar and hydro, capacity factors depend on grades, see Section Non-biomass renewables. |
Revision as of 14:21, 3 February 2017
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 <xr id="tab:REMIND_electricity_technologies"/>, 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). <figtable id="tab:REMIND_electricity_technologies">
Energy Carrier | Technology |
---|---|
Primary exhaustible resource | |
Coal |
|
Oil |
|
Gas |
|
Uranium |
|
Primary renewable resource | |
Solar |
|
Wind |
|
Hydropower |
|
Biomass |
|
Geothermal |
|
Secondary energy type | |
Hydrogen |
|
</figtable>
<figure id="fig:REMINDtable_4"> </figure>
Table 2. 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).
<figtable id="tab:REMINDtable_5"> </figtable>
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 [1].
The techno-economic parameters of power technologies used in the model are given in <xr id="tab:REMINDtable_5"/> for fuel-based technologies and <xr id="tab:REMINDtable_6"/> 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 (Neij et al. 2003; Nitsch et al. 2004; IEA 2007a; Junginger et al. 2008; Pietzcker et al. 2014).
<figtable id="tab:REMINDtable_6"> </figtable>
- ↑ Sullivan et al. (2013)