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Game-Theoretic Modeling of Electricity Markets in Central Europe

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Abstract

The paper deals with the methodology of computer modeling and simulation of complex markets with electricity and related products. The methodology is presented using a particular configuration of Central European markets with decentralized trading and international electricity transfers. The modeling approach is based on pure computer numerical solution in discrete state space determined by problems on which the modeled players are expected to decide—price offered for electricity supplied to various markets, breakdown of total power generation into individual commodities (yearly band, monthly band, spinning reserve) and setting bids in auctions for cross-border profiles. Similar approach to decision-making is adopted on the buyer’s side. Buyers are expected to strive to contract power supplies in the way that is most advantageous for them. The generated state space is then analyzed using concepts of mathematical game theory. In this way, we obtain a prediction of probable decisions of modeled player s in their market competition. Finally, we present a simplified power system forecast for Central Europe for year 2009.

Suggested Citation

  • Martin Hrubý & Petr Čambala & Jan Toufar, 2010. "Game-Theoretic Modeling of Electricity Markets in Central Europe," Czech Economic Review, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, vol. 4(1), pages 032-061, March.
  • Handle: RePEc:fau:aucocz:au2010_032
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    References listed on IDEAS

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    1. Green, Kesten C., 2002. "Forecasting decisions in conflict situations: a comparison of game theory, role-playing, and unaided judgement," International Journal of Forecasting, Elsevier, vol. 18(3), pages 321-344.
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    3. Larry Samuelson, 2004. "Modeling Knowledge in Economic Analysis," Journal of Economic Literature, American Economic Association, vol. 42(2), pages 367-403, June.
    4. Krishna, Vijay, 2009. "Auction Theory," Elsevier Monographs, Elsevier, edition 2, number 9780123745071.
    5. Erev, Ido & Roth, Alvin E. & Slonim, Robert L. & Barron, Greg, 2002. "Predictive value and the usefulness of game theoretic models," International Journal of Forecasting, Elsevier, vol. 18(3), pages 359-368.
    6. Marc VIELLE & Laurent VIGUIER & Alain HAURIE & Alain BERNARD, "undated". "A Two-level Computable Equilibrium Model to Assess the Strategic Allocation of Emission Allowances Within the European Union," EcoMod2004 330600153, EcoMod.
    7. Martin Hrubý, 2008. "Algorithmic Approaches to Game-theoretical Modeling and Simulation," Czech Economic Review, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, vol. 2(3), pages 268-300, December.
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    Cited by:

    1. Zakeri, Behnam & Virasjoki, Vilma & Syri, Sanna & Connolly, David & Mathiesen, Brian V. & Welsch, Manuel, 2016. "Impact of Germany's energy transition on the Nordic power market – A market-based multi-region energy system model," Energy, Elsevier, vol. 115(P3), pages 1640-1662.

    More about this item

    Keywords

    Prediction model; algorithmic game theory; modeling; electricity markets;

    JEL classification:

    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • C72 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Noncooperative Games

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