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Agent-based modeling and simulation of competitive wholesale electricity markets

Author

Listed:
  • Eric Guerci

    () (GREDEG - Groupe de Recherche en Droit, Economie et Gestion - UNS - Université Nice Sophia Antipolis (... - 2019) - COMUE UCA - COMUE Université Côte d'Azur (2015 - 2019) - CNRS - Centre National de la Recherche Scientifique - UCA - Université Côte d'Azur, GREQAM - Groupement de Recherche en Économie Quantitative d'Aix-Marseille - ECM - École Centrale de Marseille - CNRS - Centre National de la Recherche Scientifique - AMU - Aix Marseille Université - EHESS - École des hautes études en sciences sociales)

  • Mohammad Ali Rastegar

    (Chercheur indépendant)

  • Silvano Cincotti

    (DIME - Dipartimento di ingegneria meccanica, energetica, gestionale e dei trasporti - Universita degli studi di Genova)

Abstract

This paper sheds light on a promising and very active research area for electricity market modeling, that is, agent-based computational economics. The intriguing perspective of such research methodology is to succeed in tackling the complexity of the electricity market structure, thus the fast-growing literature appeared in the last decade on this field. This paper aims to present the state-of-the-art in this field by studying the evolution and by characterizing the heterogeneity of the research issues, of the modeling assumptions and of the computational techniques adopted by the several research publications reviewed.

Suggested Citation

  • Eric Guerci & Mohammad Ali Rastegar & Silvano Cincotti, 2010. "Agent-based modeling and simulation of competitive wholesale electricity markets," Post-Print halshs-00871063, HAL.
  • Handle: RePEc:hal:journl:halshs-00871063
    DOI: 10.1007/978-3-642-12686-4_9
    Note: View the original document on HAL open archive server: https://halshs.archives-ouvertes.fr/halshs-00871063
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    Citations

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    Cited by:

    1. Weron, Rafał, 2014. "Electricity price forecasting: A review of the state-of-the-art with a look into the future," International Journal of Forecasting, Elsevier, vol. 30(4), pages 1030-1081.
    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. Ringler, Philipp & Keles, Dogan & Fichtner, Wolf, 2017. "How to benefit from a common European electricity market design," Energy Policy, Elsevier, vol. 101(C), pages 629-643.
    4. Richstein, Jörn C. & Chappin, Emile J.L. & de Vries, Laurens J., 2014. "Cross-border electricity market effects due to price caps in an emission trading system: An agent-based approach," Energy Policy, Elsevier, vol. 71(C), pages 139-158.
    5. Balint, T. & Lamperti, F. & Mandel, A. & Napoletano, M. & Roventini, A. & Sapio, A., 2017. "Complexity and the Economics of Climate Change: A Survey and a Look Forward," Ecological Economics, Elsevier, vol. 138(C), pages 252-265.
    6. 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.
    7. Jean-Luc Gaffard & Mauro Napoletano, 2012. "Agent-based models and economic policy," Sciences Po publications info:hdl:2441/53r60a8s3ku, Sciences Po.
    8. 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.
    9. Balint, T. & Lamperti, F. & Mandel, A. & Napoletano, M. & Roventini, A. & Sapio, A., 2017. "Complexity and the Economics of Climate Change: A Survey and a Look Forward," Ecological Economics, Elsevier, vol. 138(C), pages 252-265.
    10. Fattahi, A. & Sijm, J. & Faaij, A., 2020. "A systemic approach to analyze integrated energy system modeling tools: A review of national models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 133(C).
    11. Anna Kowalska-Pyzalska & Katarzyna Maciejowska & Katarzyna Sznajd-Weron & Rafal Weron, 2013. "Going green: Agent-based modeling of the diffusion of dynamic electricity tariffs," HSC Research Reports HSC/13/05, Hugo Steinhaus Center, Wroclaw University of Technology.
    12. 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.
    13. Alexopoulos, Thomas A., 2017. "The growing importance of natural gas as a predictor for retail electricity prices in US," Energy, Elsevier, vol. 137(C), pages 219-233.
    14. G P Girish & Aviral Kumar Tiwari, 2016. "A comparison of different univariate forecasting models forSpot Electricity Price in India," Economics Bulletin, AccessEcon, vol. 36(2), pages 1039-1057.
    15. Bublitz, Andreas & Keles, Dogan & Fichtner, Wolf, 2017. "An analysis of the decline of electricity spot prices in Europe: Who is to blame?," Energy Policy, Elsevier, vol. 107(C), pages 323-336.
    16. Browne, Oliver & Poletti, Stephen & Young, David, 2015. "How does market power affect the impact of large scale wind investment in 'energy only' wholesale electricity markets?," Energy Policy, Elsevier, vol. 87(C), pages 17-27.
    17. 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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