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{{ModelDocumentationTemplate
{{ModelDocumentationTemplate
|IsEmpty=No
|IsEmpty=No
|IsDocumentationOf=REMIND
|IsDocumentationOf=REMIND-MAgPIE
|DocumentationCategory=Electricity
|DocumentationCategory=Electricity
}}
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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).
Around twenty electricity generation technologies are represented in REMIND-MAgPIE, see <xr id="tab:REMIND-MAgPIE_electricity_technologies"/>, with several low-carbon (CCS) and zero carbon options (nuclear and renewables).






'''Table 1'''. Energy Conversion Technologies for Electricity (Note: &dagger; indicates that technologies can be combined with CCS).
'''Table 1'''. Energy Conversion Technologies for Electricity (Note: &dagger; indicates that technologies can be combined with CCS).
<figtable id="tab:REMIND_electricity_technologies">
<figtable id="tab:REMIND-MAgPIE_electricity_technologies">
{| class="wikitable"
{| class="wikitable"
|+<caption>Energy Conversion Technologies for Electricity</caption>
|+<caption>Energy Conversion Technologies for Electricity</caption>
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</figtable>
</figtable>


<figure id="fig:REMINDtable_4">
<figure id="fig:REMIND-MAgPIEtable_4">
[[File:54067596.jpg]]
[[File:54067596.jpg]]
</figure>
</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).
'''Table 2'''. Techno-economic characteristics of technologies based on exhaustible energy sources and biomass <ref>Iwasaki W (2003) A consideration of the economic efficiency of hydrogen production from biomass. International Journal of Hydrogen Energy 28:939–944</ref>; <ref>Hamelinck C (2004) Outlook for advanced biofuels. Ph.D. Thesis, University of Utrecht</ref>; <ref>Bauer N (2005) Carbon capture and sequestration: An option to buy time? Ph.D. Thesis, University of Potsdam</ref>; <ref>Ansolabehere S, Beer J, Deutch J, et al (2007) The Future of Coal: An Interdisciplinary MIT Study. Massachusetts Institute of Technology, Cambridge, Massachusetts</ref>; <ref>Gül T, Kypreos S, Barreto L (2007) Hydrogen and Biofuels – A Modelling Analysis of Competing Energy Carriers for Western Europe. In: Proceedings of the World Energy Congress “Energy Future in an Interdependent World”. 11–15 November 2007, Rome, Italy</ref>; <ref>Ragettli M (2007) Cost outlook for the production of biofuels. Diploma Thesis, Swiss Federal Institute of Technology</ref>; <ref>Schulz T (2007) Intermediate steps towards the 2000-Watt society in Switzerland: an energy-economic scenario analysis. PhD Thesis, Swiss Federal Institute of Technology (ETH)</ref>; <ref>Uddin SN, Barreto L (2007) Biomass-fired cogeneration systems with CO2 capture and storage. Renewable Energy 32:1006–1019. doi: 10.1016/j.renene.2006.04.009</ref>; <ref>Rubin ES, Chen C, Rao AB (2007) Cost and performance of fossil fuel power plants with CO2 capture and storage. Energy Policy 35:4444–4454. doi: 10.1016/j.enpol.2007.03.009</ref>; <ref>Takeshita T, Yamaji K (2008) Important roles of Fischer-Tropsch synfuels in the global energy future. Energy Policy 36:2773–2784. doi: http://dx.doi.org/10.1016/j.enpol.2008.02.044</ref>; <ref>Brown D, Gassner M, Fuchino T, Marechal F (2009) Thermo-economic analysis for the optimal conceptual design of biomass gasification energy conversion systems. Applied Thermal Engineering</ref>; <ref>Klimantos P, Koukouzas N, Katsiadakis A, Kakaras E (2009) Air-blown biomass gasification combined cycles: System analysis and economic assessment. Energy 34:708–714</ref>; <ref>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</ref>.


<figtable id="tab:REMINDtable_5">
<figtable id="tab:REMIND-MAgPIEtable_5">
[[File:Remind Table 5.PNG]]
[[File:Remind Table 5.PNG]]
</figtable>
</figtable>
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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 <ref>Sullivan et al. (2013)</ref>.
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 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</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:REMIND-MAgPIEtable_5"/> for fuel-based technologies and <xr id="tab:REMIND-MAgPIEtable_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).
'''Table 3'''. Techno-economic characteristics of technologies based on non-biomass renewable energy sources <ref>Neij L, Andersen PD, Durstewitz M, et al (2003) Experience Curves: A Tool for Energy Policy Assessment (Extool Final Report). Lund University, Risø National Laboratory, ISET</ref>; <ref>Nitsch J, Krewitt W, Nast M, et al (2004) Ökologisch optimierter Ausbau der Nutzung erneuerbarer Energien in Deutschland (Kurzfassung). BMU, DLR, ifeu, Wuppertal Institut, Stuttgart, Heidelberg, Wuppertal</ref>; <ref>IEA (2007a) Energy Balances of OECD Countries. International Energy Agency, Paris</ref>; <ref>Junginger HM, Lako P, Lensink S, et al (2008) Technological learning in the energy sector. MNP</ref>; <ref>Pietzcker et al. 2014</ref>.


<figtable id="tab:REMINDtable_6">
<figtable id="tab:REMIND-MAgPIEtable_6">
[[File:Remind Table 6.PNG]]
[[File:Remind Table 6.PNG]]
</figtable>
</figtable>
<references />

Latest revision as of 14:34, 21 November 2021

Alert-warning.png Note: The documentation of REMIND-MAgPIE is and is not yet 'published'!

Model Documentation - REMIND-MAgPIE

    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
      Solution method
      Anticipation

      Around twenty electricity generation technologies are represented in REMIND-MAgPIE, see <xr id="tab:REMIND-MAgPIE_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-MAgPIE_electricity_technologies">

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

      </figtable>

      <figure id="fig:REMIND-MAgPIEtable_4"> 54067596.jpg </figure>

      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].

      <figtable id="tab:REMIND-MAgPIEtable_5"> Remind Table 5.PNG </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 [14].

      The techno-economic parameters of power technologies used in the model are given in <xr id="tab:REMIND-MAgPIEtable_5"/> for fuel-based technologies and <xr id="tab:REMIND-MAgPIEtable_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 [15]; [16]; [17]; [18]; [19].

      <figtable id="tab:REMIND-MAgPIEtable_6"> Remind Table 6.PNG </figtable>







      1. ↑ Iwasaki W (2003) A consideration of the economic efficiency of hydrogen production from biomass. International Journal of Hydrogen Energy 28:939–944
      2. ↑ Hamelinck C (2004) Outlook for advanced biofuels. Ph.D. Thesis, University of Utrecht
      3. ↑ Bauer N (2005) Carbon capture and sequestration: An option to buy time? Ph.D. Thesis, University of Potsdam
      4. ↑ Ansolabehere S, Beer J, Deutch J, et al (2007) The Future of Coal: An Interdisciplinary MIT Study. Massachusetts Institute of Technology, Cambridge, Massachusetts
      5. ↑ Gül T, Kypreos S, Barreto L (2007) Hydrogen and Biofuels – A Modelling Analysis of Competing Energy Carriers for Western Europe. In: Proceedings of the World Energy Congress “Energy Future in an Interdependent World”. 11–15 November 2007, Rome, Italy
      6. ↑ Ragettli M (2007) Cost outlook for the production of biofuels. Diploma Thesis, Swiss Federal Institute of Technology
      7. ↑ Schulz T (2007) Intermediate steps towards the 2000-Watt society in Switzerland: an energy-economic scenario analysis. PhD Thesis, Swiss Federal Institute of Technology (ETH)
      8. ↑ Uddin SN, Barreto L (2007) Biomass-fired cogeneration systems with CO2 capture and storage. Renewable Energy 32:1006–1019. doi: 10.1016/j.renene.2006.04.009
      9. ↑ Rubin ES, Chen C, Rao AB (2007) Cost and performance of fossil fuel power plants with CO2 capture and storage. Energy Policy 35:4444–4454. doi: 10.1016/j.enpol.2007.03.009
      10. ↑ Takeshita T, Yamaji K (2008) Important roles of Fischer-Tropsch synfuels in the global energy future. Energy Policy 36:2773–2784. doi: http://dx.doi.org/10.1016/j.enpol.2008.02.044
      11. ↑ Brown D, Gassner M, Fuchino T, Marechal F (2009) Thermo-economic analysis for the optimal conceptual design of biomass gasification energy conversion systems. Applied Thermal Engineering
      12. ↑ Klimantos P, Koukouzas N, Katsiadakis A, Kakaras E (2009) Air-blown biomass gasification combined cycles: System analysis and economic assessment. Energy 34:708–714
      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
      15. ↑ Neij L, Andersen PD, Durstewitz M, et al (2003) Experience Curves: A Tool for Energy Policy Assessment (Extool Final Report). Lund University, Risø National Laboratory, ISET
      16. ↑ Nitsch J, Krewitt W, Nast M, et al (2004) Ökologisch optimierter Ausbau der Nutzung erneuerbarer Energien in Deutschland (Kurzfassung). BMU, DLR, ifeu, Wuppertal Institut, Stuttgart, Heidelberg, Wuppertal
      17. ↑ IEA (2007a) Energy Balances of OECD Countries. International Energy Agency, Paris
      18. ↑ Junginger HM, Lako P, Lensink S, et al (2008) Technological learning in the energy sector. MNP
      19. ↑ Pietzcker et al. 2014
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