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An optimal trading problem in intraday electricity markets

Author

Listed:
  • René Aïd

    (FiME Lab - Laboratoire de Finance des Marchés d'Energie - Université Paris Dauphine-PSL - PSL - Université Paris Sciences et Lettres - CREST - EDF R&D - EDF R&D - EDF - EDF)

  • Pierre Gruet

    (LPMA - Laboratoire de Probabilités et Modèles Aléatoires - UPMC - Université Pierre et Marie Curie - Paris 6 - UPD7 - Université Paris Diderot - Paris 7 - CNRS - Centre National de la Recherche Scientifique)

  • Huyên Pham

    (LPMA - Laboratoire de Probabilités et Modèles Aléatoires - UPMC - Université Pierre et Marie Curie - Paris 6 - UPD7 - Université Paris Diderot - Paris 7 - CNRS - Centre National de la Recherche Scientifique, CREST - Centre de Recherche en Économie et Statistique - ENSAI - Ecole Nationale de la Statistique et de l'Analyse de l'Information [Bruz] - X - École polytechnique - ENSAE Paris - École Nationale de la Statistique et de l'Administration Économique - CNRS - Centre National de la Recherche Scientifique)

Abstract

We consider the problem of optimal trading for a power producer in the context of intraday electricity markets. The aim is to minimize the imbalance cost induced by the random residual demand in electricity, i.e. the consumption from the clients minus the production from renewable energy. For a simple linear price impact model and a quadratic criterion, we explicitly obtain approximate optimal strategies in the intraday market and thermal power generation, and exhibit some remarkable properties of the trading rate. Furthermore, we study the case when there are jumps on the demand forecast and on the intraday price, typically due to error in the prediction of wind power generation. Finally, we solve the problem when taking into account delay constraints in thermal power production.

Suggested Citation

  • René Aïd & Pierre Gruet & Huyên Pham, 2015. "An optimal trading problem in intraday electricity markets," Working Papers hal-01104829, HAL.
    • Handle: RePEc:hal:wpaper:hal-01104829
    Note: View the original document on HAL open archive server: https://hal.science/hal-01104829
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    References listed on IDEAS

    as
    1. Arthur Henriot, 2014. "Market Design with Centralized Wind Power Management: Handling Low-predictability in Intraday Markets," The Energy Journal, International Association for Energy Economics, vol. 0(Number 1).
    2. Garnier, Ernesto & Madlener, Reinhard, 2014. "Balancing Forecast Errors in Continuous-Trade Intraday Markets," FCN Working Papers 2/2014, E.ON Energy Research Center, Future Energy Consumer Needs and Behavior (FCN).
    3. Alain Bensoussan & Pierre Bertrand & Alexandre Brouste, 2014. "A generalized linear model approach to seasonal aspects of wind speed modeling," Journal of Applied Statistics, Taylor & Francis Journals, vol. 41(8), pages 1694-1707, August.
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    Cited by:

    1. Jens Hönen & Johann L. Hurink & Bert Zwart, 2023. "A classification scheme for local energy trading," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 45(1), pages 85-118, March.
    2. Marcel Kremer & Rüdiger Kiesel & Florentina Paraschiv, 2020. "Intraday Electricity Pricing of Night Contracts," Energies, MDPI, vol. 13(17), pages 1-14, September.

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    More about this item

    Keywords

    JEL Classification: G11; Q02; Q40;
    All these keywords.

    JEL classification:

    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • Q02 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - General - - - Commodity Market
    • Q40 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - General

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