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A new pricing scheme for a multi-period pool-based electricity auction

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  • Toczylowski, Eugeniusz
  • Zoltowska, Izabela

Abstract

A new pricing scheme is proposed for determining the social welfare distribution in a centralized pool-based auction in the context of solving the unit commitment problems under competition. A significant contribution of this paper over previous publications on this subject is the inclusion of the price-responsive demand side for the multi-period auctions with dynamic commitment characteristics. The model allows every thermal unit and every consumer to obtain individual maximum profits, and at the same time it gives the market coordinator an adequate tool for solving the ensuing technologically constrained unit commitment problem with fair market clearing. The pricing model is in the form of a mixed linear programming model that minimizes the sum of the compensation costs. The accompanying case study illustrates the approach proposed.

Suggested Citation

  • Toczylowski, Eugeniusz & Zoltowska, Izabela, 2009. "A new pricing scheme for a multi-period pool-based electricity auction," European Journal of Operational Research, Elsevier, vol. 197(3), pages 1051-1062, September.
    • Handle: RePEc:eee:ejores:v:197:y:2009:i:3:p:1051-1062
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    References listed on IDEAS

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    1. François Bouffard & Francisco D. Galiana, 2005. "Generalized Uplifts in Pool-Based Electricity Markets," Springer Books, in: El Kébir Boukas & Roland P. Malhamé (ed.), Analysis, Control and Optimization of Complex Dynamic Systems, chapter 0, pages 193-214, Springer.
    2. O'Neill, Richard P. & Sotkiewicz, Paul M. & Hobbs, Benjamin F. & Rothkopf, Michael H. & Stewart, William R., 2005. "Efficient market-clearing prices in markets with nonconvexities," European Journal of Operational Research, Elsevier, vol. 164(1), pages 269-285, July.
    3. Gerard Doorman & Bjørn Nygreen, 2003. "Market Price Calculations in Restructured Electricity Markets," Annals of Operations Research, Springer, vol. 124(1), pages 49-67, November.
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    Cited by:

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    2. Pineau, Pierre-Olivier & Rasata, Hasina & Zaccour, Georges, 2011. "Impact of some parameters on investments in oligopolistic electricity markets," European Journal of Operational Research, Elsevier, vol. 213(1), pages 180-195, August.
    3. Martin Bichler & Johannes Knörr & Felipe Maldonado, 2023. "Pricing in Nonconvex Markets: How to Price Electricity in the Presence of Demand Response," Information Systems Research, INFORMS, vol. 34(2), pages 652-675, June.
    4. David Fuller, J. & Çelebi, Emre, 2017. "Alternative models for markets with nonconvexities," European Journal of Operational Research, Elsevier, vol. 261(2), pages 436-449.
    5. Vazquez, Carlos & Hallack, Michelle & Vazquez, Miguel, 2017. "Price computation in electricity auctions with complex rules: An analysis of investment signals," Energy Policy, Elsevier, vol. 105(C), pages 550-561.
    6. Emanuel Canelas & Tânia Pinto-Varela & Bartosz Sawik, 2020. "Electricity Portfolio Optimization for Large Consumers: Iberian Electricity Market Case Study," Energies, MDPI, vol. 13(9), pages 1-21, May.
    7. Madani, Mehdi & Van Vyve, Mathieu, 2015. "Computationally efficient MIP formulation and algorithms for European day-ahead electricity market auctions," European Journal of Operational Research, Elsevier, vol. 242(2), pages 580-593.
    8. Martin Bichler & Hans Ulrich Buhl & Johannes Knörr & Felipe Maldonado & Paul Schott & Stefan Waldherr & Martin Weibelzahl, 2022. "Electricity Markets in a Time of Change: A Call to Arms for Business Research," Schmalenbach Journal of Business Research, Springer, vol. 74(1), pages 77-102, March.
    9. Zoltowska, Izabela, 2016. "Demand shifting bids in energy auction with non-convexities and transmission constraints," Energy Economics, Elsevier, vol. 53(C), pages 17-27.

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