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Pricing wind: A revenue adequate, cost recovering uniform price for electricity markets with intermittent generation

Author

Listed:
  • Zakeri, Golbon

    (Electric Power Optimization Centre, University of Auckland)

  • Pritchard, Geoff

    (Electric Power Optimization Centre, University of Auckland)

  • Bjørndal, Mette

    (Dept. of Business and Management Science, Norwegian School of Economics)

  • Bjørndal, Endre

    (Dept. of Business and Management Science, Norwegian School of Economics)

Abstract

With greater penetration of renewable generation, the uncertainty faced in electricity markets has increased substantially. Conventionally, generators are assigned a pre-dispatch quantity in advance of real time, based on estimates of uncertain quantities. Expensive real time adjustments then need to be made to ensure demand is met, as uncertainty takes on a realization. We propose a new stochastic-programming market clearing mechanism to optimize pre-dispatch quantities, given the uncertainties’ probability distribution and the costs of real-time deviation. This model differs from similar mechanisms previously proposed in that pre-dispatch quantities are not subject to any network or other physical constraints; nor do they play a role in financial settlement. We establish revenue adequacy in each scenario (as opposed to “in expectation”), welfare enhancement and expected cost recovery (including deviation costs), for this market clearing mechanism. We also establish that this market clearing mechanism is social welfare optimizing.

Suggested Citation

  • Zakeri, Golbon & Pritchard, Geoff & Bjørndal, Mette & Bjørndal, Endre, 2016. "Pricing wind: A revenue adequate, cost recovering uniform price for electricity markets with intermittent generation," Discussion Papers 2016/15, Norwegian School of Economics, Department of Business and Management Science.
    • Handle: RePEc:hhs:nhhfms:2016_015
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    File URL: http://hdl.handle.net/11250/2404525
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    References listed on IDEAS

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    1. RALPH, Daniel & SMEERS, Yves, 2015. "Risk trading and endogenous probabilities in investment equilibria," LIDAM Reprints CORE 2727, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
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    Cited by:

    1. Anna Schwele & Christos Ordoudis & Pierre Pinson & Jalal Kazempour, 2021. "Coordination of power and natural gas markets via financial instruments," Computational Management Science, Springer, vol. 18(4), pages 505-538, October.
    2. Xin Shi & Alberto J. Lamadrid L. & Luis F. Zuluaga, 2021. "Revenue Adequate Prices for Chance-Constrained Electricity Markets with Variable Renewable Energy Sources," Papers 2105.01233, arXiv.org.

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    More about this item

    Keywords

    Stochastic programming; locational pricing; wind power; regulation;
    All these keywords.

    JEL classification:

    • C60 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - General
    • L10 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - General
    • L94 - Industrial Organization - - Industry Studies: Transportation and Utilities - - - Electric Utilities

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