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A Cross-Entropy-Based Hybrid Membrane Computing Method for Power System Unit Commitment Problems

Author

Listed:
  • Min Xie

    (School of Electric Power, South China University of Technology, Guangzhou 510640, China)

  • Yuxin Du

    (State Grid Ganzhou Electric Power Supply Company, Ganzhou 341000, China)

  • Peijun Cheng

    (Guangzhou Power Supply Bureau Co., Ltd., Guangzhou 510620, China)

  • Wei Wei

    (School of Electric Power, South China University of Technology, Guangzhou 510640, China)

  • Mingbo Liu

    (School of Electric Power, South China University of Technology, Guangzhou 510640, China)

Abstract

The cross-entropy based hybrid membrane computing method is proposed in this paper to solve the power system unit commitment problem. The traditional unit commitment problem can be usually decomposed into a bi-level optimization problem including unit start-stop scheduling problem and dynamic economic dispatch problem. In this paper, the genetic algorithm-based P system is proposed to schedule the unit start-stop plan, and the biomimetic membrane computing method combined with the cross-entropy is proposed to solve the dynamic economic dispatch problem with a unit start-stop plan given. The simulation results of 10–100 unit systems for 24 h day-ahead dispatching show that the unit commitment problem can be solved effectively by the proposed cross-entropy based hybrid membrane computing method and obtain a good and stable solution.

Suggested Citation

  • Min Xie & Yuxin Du & Peijun Cheng & Wei Wei & Mingbo Liu, 2019. "A Cross-Entropy-Based Hybrid Membrane Computing Method for Power System Unit Commitment Problems," Energies, MDPI, vol. 12(3), pages 1-18, February.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:3:p:486-:d:203239
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    References listed on IDEAS

    as
    1. Reuven Rubinstein, 1999. "The Cross-Entropy Method for Combinatorial and Continuous Optimization," Methodology and Computing in Applied Probability, Springer, vol. 1(2), pages 127-190, September.
    2. Dirk P. Kroese & Sergey Porotsky & Reuven Y. Rubinstein, 2006. "The Cross-Entropy Method for Continuous Multi-Extremal Optimization," Methodology and Computing in Applied Probability, Springer, vol. 8(3), pages 383-407, September.
    3. Bai, Yang & Zhong, Haiwang & Xia, Qing & Kang, Chongqing & Xie, Le, 2015. "A decomposition method for network-constrained unit commitment with AC power flow constraints," Energy, Elsevier, vol. 88(C), pages 595-603.
    4. Pereira, Sérgio & Ferreira, Paula & Vaz, A.I.F., 2015. "A simplified optimization model to short-term electricity planning," Energy, Elsevier, vol. 93(P2), pages 2126-2135.
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    Cited by:

    1. Francisco G. Montoya & Raúl Baños & Alfredo Alcayde & Francisco Manzano-Agugliaro, 2019. "Optimization Methods Applied to Power Systems," Energies, MDPI, vol. 12(12), pages 1-8, June.

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