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Commitment of Electric Power Generators Under Stochastic Market Prices

Author

Listed:
  • Jorge Valenzuela

    (Department of Industrial and Systems Engineering, Auburn University, Auburn, Alabama 36849-5346)

  • Mainak Mazumdar

    (Department of Industrial Engineering, University of Pittsburgh, Pittsburgh, Pennsylvania 15261)

Abstract

A formulation for the commitment of electric power generators under a deregulated electricity market is proposed. The problem is expressed as a stochastic optimization problem in which expected profits are maximized while meeting demand and standard operating constraints. Under an assumption of perfect competition, when an electric power producer has the option of trading electricity at market prices, a unit commitment schedule can be obtained by optimizing the self-commitment of each unit separately subject to stochastic prices. Three certainty-equivalent formulations of the stochastic self-commitment problem are provided. The procedures involve application of dynamic programming, statistical analysis, and asymptotic probability computations. The price of electricity is represented by a stochastic model depending on demand, generating unit reliabilities, and temperature fluctuations. We use several approximation methods (normal, Edgeworth series expansion, and Monte Carlo simulation) for computing the required probability distributions. Numerical examples are provided for a market consisting of 150 generating units.

Suggested Citation

  • Jorge Valenzuela & Mainak Mazumdar, 2003. "Commitment of Electric Power Generators Under Stochastic Market Prices," Operations Research, INFORMS, vol. 51(6), pages 880-893, December.
    • Handle: RePEc:inm:oropre:v:51:y:2003:i:6:p:880-893
    DOI: 10.1287/opre.51.6.880.24924
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    References listed on IDEAS

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    1. Jonathan F. Bard, 1988. "Short-Term Scheduling of Thermal-Electric Generators Using Lagrangian Relaxation," Operations Research, INFORMS, vol. 36(5), pages 756-766, October.
    2. Samer Takriti & Benedikt Krasenbrink & Lilian S.-Y. Wu, 2000. "Incorporating Fuel Constraints and Electricity Spot Prices into the Stochastic Unit Commitment Problem," Operations Research, INFORMS, vol. 48(2), pages 268-280, April.
    3. repec:aen:journl:1998v19-03-a02 is not listed on IDEAS
    4. Edward Kahn, 1995. "Regulation by Simulation: The Role of Production Cost Models in Electricity Planning and Pricing," Operations Research, INFORMS, vol. 43(3), pages 388-398, June.
    Full references (including those not matched with items on IDEAS)

    Citations

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    Cited by:

    1. Kai Pan & Yongpei Guan, 2022. "Integrated Stochastic Optimal Self-Scheduling for Two-Settlement Electricity Markets," INFORMS Journal on Computing, INFORMS, vol. 34(3), pages 1819-1840, May.
    2. Li, Gong & Shi, Jing & Qu, Xiuli, 2011. "Modeling methods for GenCo bidding strategy optimization in the liberalized electricity spot market–A state-of-the-art review," Energy, Elsevier, vol. 36(8), pages 4686-4700.
    3. Ghaninejad, Mousa, 2020. "عرضه، تقاضا، و پیشنهاد قیمت در بازار برق ایران [Supply, Demand, and Bidding in Iran’s Electricity Market]," MPRA Paper 105340, University Library of Munich, Germany.
    4. Melamed, Michal & Ben-Tal, Aharon & Golany, Boaz, 2018. "A multi-period unit commitment problem under a new hybrid uncertainty set for a renewable energy source," Renewable Energy, Elsevier, vol. 118(C), pages 909-917.
    5. Jiang, Ruiwei & Zhang, Muhong & Li, Guang & Guan, Yongpei, 2014. "Two-stage network constrained robust unit commitment problem," European Journal of Operational Research, Elsevier, vol. 234(3), pages 751-762.
    6. Guthrie, Graeme & Videbeck, Steen, 2007. "Electricity spot price dynamics: Beyond financial models," Energy Policy, Elsevier, vol. 35(11), pages 5614-5621, November.
    7. Briest, Gordon & Lauven, Lars-Peter & Kupfer, Stefan & Lukas, Elmar, 2022. "Leaving well-worn paths: Reversal of the investment-uncertainty relationship and flexible biogas plant operation," European Journal of Operational Research, Elsevier, vol. 300(3), pages 1162-1176.

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