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Pricing Under Uncertainty in Multi-Interval Real-Time Markets

Author

Listed:
  • Jehum Cho

    (Center for Operations Research and Econometrics (CORE), Université Catholique de Louvain (UCLouvain), 1348 Louvain-la-Neuve, Belgium;)

  • Anthony Papavasiliou

    (Center for Operations Research and Econometrics (CORE), Université Catholique de Louvain (UCLouvain), 1348 Louvain-la-Neuve, Belgium)

Abstract

Recent research has demonstrated that real-time auctions can generate the need for side payments, even if the market clearing models are convex, because of the rolling nature of real-time market clearing. This observation has inspired proposals for modifying the real-time market-clearing model in order to account for binding past decisions. We extend this analysis in order to account for uncertainty by proposing a real-time market-clearing model with look-ahead and an endogenous representation of uncertainty. We define two different types of expected lost opportunity cost as performance metrics. Our market-clearing model provides the price signal minimizing one of these metrics using the Stochastic Gradient Descent algorithm. We present results from a case study of the ISO New England system under a scenario of significant renewable energy penetration while accounting for ramp rates, storage, and transmission constraints.

Suggested Citation

  • Jehum Cho & Anthony Papavasiliou, 2023. "Pricing Under Uncertainty in Multi-Interval Real-Time Markets," Operations Research, INFORMS, vol. 71(6), pages 1928-1942, November.
    • Handle: RePEc:inm:oropre:v:71:y:2023:i:6:p:1928-1942
    DOI: 10.1287/opre.2022.2314
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