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Inverse Optimization for the Recovery of Market Structure from Market Outcomes: An Application to the MISO Electricity Market

Author

Listed:
  • John R. Birge

    (Booth School of Business, University of Chicago, Chicago, Illinois, 60637)

  • Ali Hortaçsu

    (Department of Economics, University of Chicago, Chicago, Illinois, 60637)

  • J. Michael Pavlin

    (Lazaridis School of Business and Economics, Wilfrid Laurier University, Waterloo, Ontario N2L 3C5, Canada)

Abstract

We propose an inverse optimization-based methodology to determine market structure from commodity and transportation prices. The methods are appropriate for locational marginal price -based electricity markets where prices are shadow prices in the centralized optimization used to clear the market. We apply the inverse optimization methodology to outcome data from the Midcontinent ISO electricity market (MISO) and, under noise-free assumptions, recover parameters of transmission and related constraints that are not revealed to market participants but explain the price variation. We demonstrate and evaluate analytical uses of the recovered structure including reconstruction of the pricing mechanism and investigations of locational market power through the transmission constrained residual demand derivative. Prices generated from the reconstructed mechanism are highly correlated to actual MISO prices under a wide variety of market conditions. In a case study, the residual demand derivative is shown to be correlated with coefficients of certain transmission constraints.

Suggested Citation

  • John R. Birge & Ali Hortaçsu & J. Michael Pavlin, 2017. "Inverse Optimization for the Recovery of Market Structure from Market Outcomes: An Application to the MISO Electricity Market," Operations Research, INFORMS, vol. 65(4), pages 837-855, August.
    • Handle: RePEc:inm:oropre:v:65:y:2017:i:4:p:837-855
    DOI: 10.1287/opre.2017.1606
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    Cited by:

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    5. Lili Zhang & Zhengrui Chen & Dan Shi & Yanan Zhao, 2023. "An Inverse Optimal Value Approach for Synchronously Optimizing Activity Durations and Worker Assignments with a Project Ideal Cost," Mathematics, MDPI, vol. 11(5), pages 1-21, February.
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    7. Katzen, Matthew & Leslie, Gordon W., 2024. "Siting and operating incentives in electrical networks: A study of mispricing in zonal markets," International Journal of Industrial Organization, Elsevier, vol. 94(C).
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    10. Stathis Tompaidis, 2021. "Comments on “Network Structure and Its Impact on Commodity Markets”," Production and Operations Management, Production and Operations Management Society, vol. 30(12), pages 4577-4578, December.
    11. John R. Birge, 2021. "Network Structure and its Impact on Commodity Markets," Production and Operations Management, Production and Operations Management Society, vol. 30(12), pages 4568-4574, December.
    12. Timothy C. Y. Chan & Taewoo Lee & Daria Terekhov, 2019. "Inverse Optimization: Closed-Form Solutions, Geometry, and Goodness of Fit," Management Science, INFORMS, vol. 65(3), pages 1115-1135, March.
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    14. Zhu, Zhirun & Yang, Zhifang & Wang, Yi & Yu, Juan, 2025. "Reveal branch flow scarcity from limited electricity market information," Energy, Elsevier, vol. 338(C).
    15. Merve Bodur & Timothy C. Y. Chan & Ian Yihang Zhu, 2022. "Inverse Mixed Integer Optimization: Polyhedral Insights and Trust Region Methods," INFORMS Journal on Computing, INFORMS, vol. 34(3), pages 1471-1488, May.
    16. Rishabh Gupta & Qi Zhang, 2022. "Decomposition and Adaptive Sampling for Data-Driven Inverse Linear Optimization," INFORMS Journal on Computing, INFORMS, vol. 34(5), pages 2720-2735, September.
    17. Zahed Shahmoradi & Taewoo Lee, 2022. "Quantile Inverse Optimization: Improving Stability in Inverse Linear Programming," Operations Research, INFORMS, vol. 70(4), pages 2538-2562, July.
    18. John R. Birge & Timothy C. Y. Chan & J. Michael Pavlin & Ian Yihang Zhu, 2022. "Spatial Price Integration in Commodity Markets with Capacitated Transportation Networks," Operations Research, INFORMS, vol. 70(3), pages 1739-1761, May.
    19. Mahler, Valentin & Girard, Robin & Kariniotakis, Georges, 2022. "Data-driven structural modeling of electricity price dynamics," Energy Economics, Elsevier, vol. 107(C).
    20. Jonathan Yu-Meng Li, 2021. "Inverse Optimization of Convex Risk Functions," Management Science, INFORMS, vol. 67(11), pages 7113-7141, November.
    21. Javad Tayyebi & Ali Reza Sepasian, 2020. "Partial inverse min–max spanning tree problem," Journal of Combinatorial Optimization, Springer, vol. 40(4), pages 1075-1091, November.
    22. Vusal Babashov & Antoine Sauré & Onur Ozturk & Jonathan Patrick, 2023. "Setting wait time targets in a multi‐priority patient setting," Production and Operations Management, Production and Operations Management Society, vol. 32(6), pages 1958-1974, June.
    23. Timothy C. Y. Chan & Rafid Mahmood & Ian Yihang Zhu, 2025. "Inverse Optimization: Theory and Applications," Operations Research, INFORMS, vol. 73(2), pages 1046-1074, March.
    24. Ghobadi, Kimia & Mahmoudzadeh, Houra, 2021. "Inferring linear feasible regions using inverse optimization," European Journal of Operational Research, Elsevier, vol. 290(3), pages 829-843.

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