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Which model features matter? An experimental approach to evaluate power market modeling choices

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  • Siala, Kais
  • Mier, Mathias
  • Schmidt, Lukas
  • Torralba-Díaz, Laura
  • Sheykhha, Siamak
  • Savvidis, Georgios

Abstract

A novel experimental approach of inter- and intramodel comparisons is conducted with five power market models to give recommendations for modelers working on decarbonization pathways of Europe until 2050. The experiments investigate the impact of model type (optimization vs. simulation), planning horizon (intertemporal vs. myopic), temporal resolution (8760 vs. 384 h), and spatial resolution (28 countries vs. 12 mega-regions). The model type fundamentally determines the evolution of capacity expansion. Planning horizon (assumed foresight of firms) plays a minor role for scenarios with high carbon prices. For low carbon prices in turn, results from myopic models deviate considerably from those of intertemporal models. Lower temporal and spatial resolutions foster wind power via storage and via neglected transmission boundaries, respectively. Using simulation instead of optimization frameworks, a shorter planning horizon of firms, or lower temporal and spatial resolutions might be necessary to reduce the computational complexity. This paper delivers recommendations on how to limit the discrepancies in such cases.

Suggested Citation

  • Siala, Kais & Mier, Mathias & Schmidt, Lukas & Torralba-Díaz, Laura & Sheykhha, Siamak & Savvidis, Georgios, 2022. "Which model features matter? An experimental approach to evaluate power market modeling choices," Energy, Elsevier, vol. 245(C).
    • Handle: RePEc:eee:energy:v:245:y:2022:i:c:s0360544222002043
    DOI: 10.1016/j.energy.2022.123301
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    1. van Vuuren, Detlef P. & Hoogwijk, Monique & Barker, Terry & Riahi, Keywan & Boeters, Stefan & Chateau, Jean & Scrieciu, Serban & van Vliet, Jasper & Masui, Toshihiko & Blok, Kornelis & Blomen, Eliane , 2009. "Comparison of top-down and bottom-up estimates of sectoral and regional greenhouse gas emission reduction potentials," Energy Policy, Elsevier, vol. 37(12), pages 5125-5139, December.
    2. Kenneth Gillingham & William D. Nordhaus & David Anthoff & Geoffrey Blanford & Valentina Bosetti & Peter Christensen & Haewon McJeon & John Reilly & Paul Sztorc, 2015. "Modeling Uncertainty in Climate Change: A Multi-Model Comparison," NBER Working Papers 21637, National Bureau of Economic Research, Inc.
    3. Mier, Mathias & Weissbart, Christoph, 2020. "Power markets in transition: Decarbonization, energy efficiency, and short-term demand response," Energy Economics, Elsevier, vol. 86(C).
    4. Helgeson, Broghan & Peter, Jakob, 2020. "The role of electricity in decarbonizing European road transport – Development and assessment of an integrated multi-sectoral model," Applied Energy, Elsevier, vol. 262(C).
    5. Nahmmacher, Paul & Schmid, Eva & Hirth, Lion & Knopf, Brigitte, 2016. "Carpe diem: A novel approach to select representative days for long-term power system modeling," Energy, Elsevier, vol. 112(C), pages 430-442.
    6. Hall, Lisa M.H. & Buckley, Alastair R., 2016. "A review of energy systems models in the UK: Prevalent usage and categorisation," Applied Energy, Elsevier, vol. 169(C), pages 607-628.
    7. Priesmann, Jan & Nolting, Lars & Praktiknjo, Aaron, 2019. "Are complex energy system models more accurate? An intra-model comparison of power system optimization models," Applied Energy, Elsevier, vol. 255(C).
    8. Hannah Förster & Katja Schumacher & Enrica De Cian & Michael Hübler & Ilkka Keppo & Silvana Mima & Ronald D. Sands, 2013. "European Energy Efficiency And Decarbonization Strategies Beyond 2030 — A Sectoral Multi-Model Decomposition," Climate Change Economics (CCE), World Scientific Publishing Co. Pte. Ltd., vol. 4(supp0), pages 1-29.
    9. Bertsch, Joachim & Growitsch, Christian & Lorenczik, Stefan & Nagl, Stephan, 2016. "Flexibility in Europe's power sector — An additional requirement or an automatic complement?," Energy Economics, Elsevier, vol. 53(C), pages 118-131.
    10. Gils, Hans Christian & Pregger, Thomas & Flachsbarth, Franziska & Jentsch, Mareike & Dierstein, Constantin, 2019. "Comparison of spatially and temporally resolved energy system models with a focus on Germany's future power supply," Applied Energy, Elsevier, vol. 255(C).
    11. Hess, Denis & Wetzel, Manuel & Cao, Karl-Kiên, 2018. "Representing node-internal transmission and distribution grids in energy system models," Renewable Energy, Elsevier, vol. 119(C), pages 874-890.
    12. Srikkanth Ramachandran & Kais Siala & Cristina de La Rúa & Tobias Massier & Arif Ahmed & Thomas Hamacher, 2021. "Life Cycle Climate Change Impact of a Cost-Optimal HVDC Connection to Import Solar Energy from Australia to Singapore," Energies, MDPI, vol. 14(21), pages 1-23, November.
    13. Richter, Jan, 2011. "DIMENSION - A Dispatch and Investment Model for European Electricity Markets," EWI Working Papers 2011-3, Energiewirtschaftliches Institut an der Universitaet zu Koeln (EWI).
    14. Diaz, Gabriel & Inzunza, Andrés & Moreno, Rodrigo, 2019. "The importance of time resolution, operational flexibility and risk aversion in quantifying the value of energy storage in long-term energy planning studies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 112(C), pages 797-812.
    15. Savvidis, Georgios & Siala, Kais & Weissbart, Christoph & Schmidt, Lukas & Borggrefe, Frieder & Kumar, Subhash & Pittel, Karen & Madlener, Reinhard & Hufendiek, Kai, 2019. "The gap between energy policy challenges and model capabilities," Energy Policy, Elsevier, vol. 125(C), pages 503-520.
    16. Poncelet, Kris & Delarue, Erik & Six, Daan & Duerinck, Jan & D’haeseleer, William, 2016. "Impact of the level of temporal and operational detail in energy-system planning models," Applied Energy, Elsevier, vol. 162(C), pages 631-643.
    17. Heuberger, Clara F. & Rubin, Edward S. & Staffell, Iain & Shah, Nilay & Mac Dowell, Niall, 2017. "Power capacity expansion planning considering endogenous technology cost learning," Applied Energy, Elsevier, vol. 204(C), pages 831-845.
    18. Connolly, D. & Lund, H. & Mathiesen, B.V. & Leahy, M., 2010. "A review of computer tools for analysing the integration of renewable energy into various energy systems," Applied Energy, Elsevier, vol. 87(4), pages 1059-1082, April.
    19. Deane, J.P. & Chiodi, Alessandro & Gargiulo, Maurizio & Ó Gallachóir, Brian P., 2012. "Soft-linking of a power systems model to an energy systems model," Energy, Elsevier, vol. 42(1), pages 303-312.
    20. Pfenninger, Stefan, 2017. "Dealing with multiple decades of hourly wind and PV time series in energy models: A comparison of methods to reduce time resolution and the planning implications of inter-annual variability," Applied Energy, Elsevier, vol. 197(C), pages 1-13.
    21. Frew, Bethany A. & Jacobson, Mark Z., 2016. "Temporal and spatial tradeoffs in power system modeling with assumptions about storage: An application of the POWER model," Energy, Elsevier, vol. 117(P1), pages 198-213.
    22. Ommen, Torben & Markussen, Wiebke Brix & Elmegaard, Brian, 2014. "Comparison of linear, mixed integer and non-linear programming methods in energy system dispatch modelling," Energy, Elsevier, vol. 74(C), pages 109-118.
    23. Mathias Mier & Kais Siala & Kristina Govorukha & Philip Mayer, 2020. "Costs and Benefits of Political and Physical Collaboration in the European Power Market," ifo Working Paper Series 343, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
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