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Solving certain complementarity problems in power markets via convex programming

Author

Listed:
  • G. Constante-Flores

    (The Ohio State University)

  • A. J. Conejo

    (The Ohio State University)

  • S. Constante-Flores

    (University of Campinas, UNICAMP)

Abstract

We address the solution of certain Mathematical Programs with Equilibrium Constraints (MPECs) in power markets using convex optimization. These MPECs constitute a class of complementarity problems relevant to the design and operation of power markets. Specifically, given a non-convex continuous MPEC of the considered type, we iteratively solve a collection of convex optimization problems that approximate the MPEC until a pre-specified tolerance is reached. We use an insightful example to illustrate the proposed solution technique and a case study to analyze its computational performance.

Suggested Citation

  • G. Constante-Flores & A. J. Conejo & S. Constante-Flores, 2022. "Solving certain complementarity problems in power markets via convex programming," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 30(3), pages 465-491, October.
    • Handle: RePEc:spr:topjnl:v:30:y:2022:i:3:d:10.1007_s11750-022-00627-3
    DOI: 10.1007/s11750-022-00627-3
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    References listed on IDEAS

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    1. Thomas Kleinert & Martin Schmidt, 2023. "Why there is no need to use a big-M in linear bilevel optimization: a computational study of two ready-to-use approaches," Computational Management Science, Springer, vol. 20(1), pages 1-12, December.

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