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Strategic bidding for multiple price-maker hydroelectric producers

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  • Gregory Steeger
  • Steffen Rebennack

Abstract

In a market comprised of multiple price-maker firms, the payoff each firm receives depends not only on one’s own actions but also on the actions of the other firms. This is the defining characteristic of a non-cooperative economic game. In this article, we ask: What is the revenue-maximizing production schedule for multiple price-maker hydroelectric producers competing in a deregulated, bid-based market? In every time stage, we seek a set of bids such that, given all other price-maker producers’ bids, no price-maker can improve (increase) their revenue by changing their bid; i.e., a pure-strategy Nash–Cournot equilibrium. From a theoretical game theory perspective, the analysis on the underlying non-cooperative game is lacking. Specifically, existing approaches are not able to detect when multiple equilibria exist and consider any equilibrium found optimal. In our approach, we create interpolations for each price-maker’s best response function using mixed-integer linear programming formulations within a dynamic programming framework. In the presence of multiple Nash equilibria, when one exists, our approach finds the equilibrium that is Pareto optimal. If a Pareto-optimal Nash equilibrium does not exist, we use a tailored bargaining algorithm to determine a unique solution. To illustrate some of the finer details of our method, we present three examples and a case study on an electricity market in Honduras.

Suggested Citation

  • Gregory Steeger & Steffen Rebennack, 2015. "Strategic bidding for multiple price-maker hydroelectric producers," IISE Transactions, Taylor & Francis Journals, vol. 47(9), pages 1013-1031, September.
  • Handle: RePEc:taf:uiiexx:v:47:y:2015:i:9:p:1013-1031
    DOI: 10.1080/0740817X.2014.1001928
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    Citations

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    Cited by:

    1. Zhong, Zhiming & Fan, Neng & Wu, Lei, 2023. "A hybrid robust-stochastic optimization approach for day-ahead scheduling of cascaded hydroelectric system in restructured electricity market," European Journal of Operational Research, Elsevier, vol. 306(2), pages 909-926.
    2. Steeger, Gregory & Rebennack, Steffen, 2017. "Dynamic convexification within nested Benders decomposition using Lagrangian relaxation: An application to the strategic bidding problem," European Journal of Operational Research, Elsevier, vol. 257(2), pages 669-686.
    3. Hassan Shavandi & Mehrdad Pirnia & J. David Fuller, 2018. "Extended opportunity cost model to find near equilibrium electricity prices under non-convexities," Papers 1809.09734, arXiv.org.
    4. Lohmann, Timo & Hering, Amanda S. & Rebennack, Steffen, 2016. "Spatio-temporal hydro forecasting of multireservoir inflows for hydro-thermal scheduling," European Journal of Operational Research, Elsevier, vol. 255(1), pages 243-258.
    5. M. Hosein Zare & Osman Y. Özaltın & Oleg A. Prokopyev, 2018. "On a class of bilevel linear mixed-integer programs in adversarial settings," Journal of Global Optimization, Springer, vol. 71(1), pages 91-113, May.
    6. Löschenbrand, Markus, 2020. "Finding multiple Nash equilibria via machine learning-supported Gröbner bases," European Journal of Operational Research, Elsevier, vol. 284(3), pages 1178-1189.
    7. Escudero, Laureano F. & Monge, Juan F. & Rodríguez-Chía, Antonio M., 2020. "On pricing-based equilibrium for network expansion planning. A multi-period bilevel approach under uncertainty," European Journal of Operational Research, Elsevier, vol. 287(1), pages 262-279.
    8. Shavandi, Hassan & Pirnia, Mehrdad & Fuller, J. David, 2019. "Extended opportunity cost model to find near equilibrium electricity prices under non-convexities," Applied Energy, Elsevier, vol. 240(C), pages 251-264.
    9. Claudia Condemi & Loretta Mastroeni & Pierluigi Vellucci, 2021. "The impact of Clean Spark Spread expectations on storage hydropower generation," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 44(2), pages 1111-1146, December.

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