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On some advantages of convex hull pricing for the European electricity auction

Author

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  • Stevens, Nicolas
  • Papavasiliou, Anthony
  • Smeers, Yves

Abstract

Since the liberalization of the power sector and the creation of wholesale electricity markets, the question of how to price the non-convexities that are present in the market has attracted the interest of both academics and practitioners. Over the years, US markets have studied and adopted different and evolving pricing rules. Since the “Trilateral Market Coupling” (2006), the European day-ahead market has opted for a notably different pricing rule. Recently, EU stakeholders have undertaken research to reform it, and have indicated an interest for some approaches that are discussed in the other side of the Atlantic. Our paper aims at contributing to the debate. We analyse six different pricing methods. We establish several mathematical properties for enabling their accurate comparison. Our findings are illustrated on stylized examples and numerical simulations that are performed on realistic datasets. Both theoretical and numerical evidences that are gathered in our paper point towards the advantages of convex hull pricing.

Suggested Citation

  • Stevens, Nicolas & Papavasiliou, Anthony & Smeers, Yves, 2024. "On some advantages of convex hull pricing for the European electricity auction," Energy Economics, Elsevier, vol. 134(C).
    • Handle: RePEc:eee:eneeco:v:134:y:2024:i:c:s0140988324002500
    DOI: 10.1016/j.eneco.2024.107542
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    References listed on IDEAS

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    1. Stevens, Nicolas & Smeers, Yves & Papavasiliou, Anthony, 2024. "Indivisibilities in investment and the role of a capacity market," LIDAM Reprints CORE 3281, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    2. Nicolas Stevens & Yves Smeers & Anthony Papavasiliou, 2024. "Indivisibilities in investment and the role of a capacity market," Journal of Regulatory Economics, Springer, vol. 66(2), pages 238-272, December.
    3. Starr, Ross M, 1969. "Quasi-Equilibria in Markets with Non-Convex Preferences," Econometrica, Econometric Society, vol. 37(1), pages 25-38, January.
    4. Bernard Knueven & James Ostrowski & Jean-Paul Watson, 2020. "On Mixed-Integer Programming Formulations for the Unit Commitment Problem," INFORMS Journal on Computing, INFORMS, vol. 32(4), pages 857-876, October.
    5. Byers, Conleigh & Hug, Gabriela, 2023. "Long-run optimal pricing in electricity markets with non-convex costs," European Journal of Operational Research, Elsevier, vol. 307(1), pages 351-363.
    6. Stevens, Nicolas & Papavasiliou, Anthony, 2022. "Application of the Level Method for Computing Locational Convex Hull Prices," LIDAM Reprints CORE 3196, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    7. Panagiotis Andrianesis & Dimitris Bertsimas & Michael C. Caramanis & William W. Hogan, 2020. "Computation of Convex Hull Prices in Electricity Markets with Non-Convexities using Dantzig-Wolfe Decomposition," Papers 2012.13331, arXiv.org, revised Oct 2021.
    8. Hung-po Chao, 2019. "Incentives for efficient pricing mechanism in markets with non-convexities," Journal of Regulatory Economics, Springer, vol. 56(1), pages 33-58, August.
    9. VAN VYVE, Mathieu, 2011. "Linear prices for non-convex electricity markets: models and algorithms," LIDAM Discussion Papers CORE 2011050, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    10. George Liberopoulos & Panagiotis Andrianesis, 2016. "Critical Review of Pricing Schemes in Markets with Non-Convex Costs," Operations Research, INFORMS, vol. 64(1), pages 17-31, February.
    11. Stevens, Nicolas & Papavasiliou, Anthony, 2022. "Application of the Level Method for Computing Locational Convex Hull Prices," LIDAM Discussion Papers CORE 2022002, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    12. O'Neill, Richard P. & Sotkiewicz, Paul M. & Hobbs, Benjamin F. & Rothkopf, Michael H. & Stewart, William R., 2005. "Efficient market-clearing prices in markets with nonconvexities," European Journal of Operational Research, Elsevier, vol. 164(1), pages 269-285, July.
    13. Mays, Jacob & Morton, David P. & O’Neill, Richard P., 2021. "Investment effects of pricing schemes for non-convex markets," European Journal of Operational Research, Elsevier, vol. 289(2), pages 712-726.
    14. Leonardo Meeus, 2020. "The Evolution of Electricity Markets in Europe," Books, Edward Elgar Publishing, number 19187.
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    More about this item

    Keywords

    Convex hull pricing; Non-uniform pricing; Non-convexities; European electricity market;
    All these keywords.

    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • D41 - Microeconomics - - Market Structure, Pricing, and Design - - - Perfect Competition
    • D44 - Microeconomics - - Market Structure, Pricing, and Design - - - Auctions
    • D47 - Microeconomics - - Market Structure, Pricing, and Design - - - Market Design
    • Q41 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Demand and Supply; Prices

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