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Agent-based simulation of electricity markets: a literature review

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  • Sensfuß, Frank
  • Ragwitz, Mario
  • Genoese, Massimo
  • Möst, Dominik

Abstract

Liberalisation, climate policy and promotion of renewable energy are challenges to players of the electricity sector in many countries. Policy makers have to consider issues like market power, bounded rationality of players and the appearance of fluctuating energy sources in order to provide adequate legislation. Furthermore the interactions between markets and environmental policy instruments become an issue of increasing importance. A promising approach for the scientific analysis of these developments is the field of agent-based simulation. The goal of this article is to provide an overview of the current work applying this methodology to the analysis of electricity markets.

Suggested Citation

  • Sensfuß, Frank & Ragwitz, Mario & Genoese, Massimo & Möst, Dominik, 2007. "Agent-based simulation of electricity markets: a literature review," Working Papers "Sustainability and Innovation" S5/2007, Fraunhofer Institute for Systems and Innovation Research (ISI).
    • Handle: RePEc:zbw:fisisi:s52007
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    1. Koppelaar, Rembrandt H.E.M. & Keirstead, James & Shah, Nilay & Woods, Jeremy, 2016. "A review of policy analysis purpose and capabilities of electricity system models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 59(C), pages 1531-1544.
    2. Kraan, Oscar & Kramer, Gert Jan & Nikolic, Igor & Chappin, Emile & Koning, Vinzenz, 2019. "Why fully liberalised electricity markets will fail to meet deep decarbonisation targets even with strong carbon pricing," Energy Policy, Elsevier, vol. 131(C), pages 99-110.
    3. Safarzynska, Karolina & van den Bergh, Jeroen C.J.M., 2011. "Industry evolution, rational agents and the transition to sustainable electricity production," Energy Policy, Elsevier, vol. 39(10), pages 6440-6452, October.
    4. Will, Christian & Zimmermann, Florian & Ensslen, Axel & Fraunholz, Christoph & Jochem, Patrick & Keles, Dogan, 2024. "Can electric vehicle charging be carbon neutral? Uniting smart charging and renewables," Applied Energy, Elsevier, vol. 371(C).
    5. Herrmann, J.K. & Savin, I., 2017. "Optimal policy identification: Insights from the German electricity market," Technological Forecasting and Social Change, Elsevier, vol. 122(C), pages 71-90.
    6. Laura Torralba-Díaz & Christoph Schimeczek & Matthias Reeg & Georgios Savvidis & Marc Deissenroth-Uhrig & Felix Guthoff & Benjamin Fleischer & Kai Hufendiek, 2020. "Identification of the Efficiency Gap by Coupling a Fundamental Electricity Market Model and an Agent-Based Simulation Model," Energies, MDPI, vol. 13(15), pages 1-19, July.
    7. Milad Maralani & Milad Maralani & Basil Sharp & Golbon Zakeri, 2016. "The Potential Impact of Industrial Energy Savings on The New Zealand Economy," EcoMod2016 9308, EcoMod.
    8. Herrmann, Johannes & Savin, Ivan, 2015. "Evolution of the electricity market in Germany: Identifying policy implications by an agent-based model," VfS Annual Conference 2015 (Muenster): Economic Development - Theory and Policy 112959, Verein für Socialpolitik / German Economic Association.
    9. Will, Christian & Zimmermann, Florian & Ensslen, Axel & Fraunholz, Christoph & Jochem, Patrick & Keles, Dogan, 2023. "Can electric vehicle charging be carbon neutral? Uniting smart charging and renewables," Working Paper Series in Production and Energy 69, Karlsruhe Institute of Technology (KIT), Institute for Industrial Production (IIP).
    10. Broeer, Torsten & Fuller, Jason & Tuffner, Francis & Chassin, David & Djilali, Ned, 2014. "Modeling framework and validation of a smart grid and demand response system for wind power integration," Applied Energy, Elsevier, vol. 113(C), pages 199-207.
    11. Frank Beckenbach & Maria Daskalakis & David Hofmann, 2018. "Agent-Based Analysis of Industrial Dynamics and Paths of Environmental Policy: The Case of Non-renewable Energy Production in Germany," Computational Economics, Springer;Society for Computational Economics, vol. 52(3), pages 953-994, October.
    12. Kraan, O. & Kramer, G.J. & Nikolic, I., 2018. "Investment in the future electricity system - An agent-based modelling approach," Energy, Elsevier, vol. 151(C), pages 569-580.
    13. Kueppers, Martin & Paredes Pineda, Stephany Nicole & Metzger, Michael & Huber, Matthias & Paulus, Simon & Heger, Hans Joerg & Niessen, Stefan, 2021. "Decarbonization pathways of worldwide energy systems – Definition and modeling of archetypes," Applied Energy, Elsevier, vol. 285(C).
    14. Arango, Santiago & Larsen, Erik, 2011. "Cycles in deregulated electricity markets: Empirical evidence from two decades," Energy Policy, Elsevier, vol. 39(5), pages 2457-2466, May.
    15. Gaivoronskaia, E. & Tsyplakov, A., 2018. "Using a Modified Erev-Roth Algorithm in an Agent-Based Electricity Market Model," Journal of the New Economic Association, New Economic Association, vol. 39(3), pages 55-83.
    16. Weiss, Olga & Bogdanov, Dmitry & Salovaara, Kaisa & Honkapuro, Samuli, 2017. "Market designs for a 100% renewable energy system: Case isolated power system of Israel," Energy, Elsevier, vol. 119(C), pages 266-277.
    17. Weiss, Olga & Pareschi, Giacomo & Georges, Gil & Boulouchos, Konstantinos, 2021. "The Swiss energy transition: Policies to address the Energy Trilemma," Energy Policy, Elsevier, vol. 148(PA).
    18. Bunn, Derek & Yusupov, Tim, 2015. "The progressive inefficiency of replacing renewable obligation certificates with contracts-for-differences in the UK electricity market," Energy Policy, Elsevier, vol. 82(C), pages 298-309.
    19. Haghnevis, Moeed & Askin, Ronald G. & Armbruster, Dieter, 2016. "An agent-based modeling optimization approach for understanding behavior of engineered complex adaptive systems," Socio-Economic Planning Sciences, Elsevier, vol. 56(C), pages 67-87.
    20. Marc Deissenroth & Martin Klein & Kristina Nienhaus & Matthias Reeg, 2017. "Assessing the Plurality of Actors and Policy Interactions: Agent-Based Modelling of Renewable Energy Market Integration," Complexity, Hindawi, vol. 2017, pages 1-24, December.
    21. Rosen, Christiane & Madlener, Reinhard, 2012. "Auction Design for Local Reserve Energy Markets," FCN Working Papers 7/2012, E.ON Energy Research Center, Future Energy Consumer Needs and Behavior (FCN), revised Mar 2013.
    22. Cristian Zambrano & Yris Olaya, 2017. "An agent-based simulation approach to congestion management for the Colombian electricity market," Annals of Operations Research, Springer, vol. 258(2), pages 217-236, November.
    23. Ringler, Philipp & Keles, Dogan & Fichtner, Wolf, 2016. "Agent-based modelling and simulation of smart electricity grids and markets – A literature review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 57(C), pages 205-215.

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