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An Improved Constrained Order Optimization Algorithm for Uncertain SCUC Problem Solving

Author

Listed:
  • Junjie Jia

    (New Energy Micro-grid Collaborative Innovation Centre of Hubei Province, China Three Gorges University, Yichang 443002, China)

  • Nan Yang

    (New Energy Micro-grid Collaborative Innovation Centre of Hubei Province, China Three Gorges University, Yichang 443002, China)

  • Chao Xing

    (Electric Power Research Institute, Yunnan Power Grid Co., Ltd., Kunming 650217, China)

  • Haoze Chen

    (State Grid Yichang Power Supply Company, State Grid Hubei Electric power CO., Ltd., Yichang 443000, China)

  • Songkai Liu

    (New Energy Micro-grid Collaborative Innovation Centre of Hubei Province, China Three Gorges University, Yichang 443002, China)

  • Yuehua Huang

    (New Energy Micro-grid Collaborative Innovation Centre of Hubei Province, China Three Gorges University, Yichang 443002, China)

  • Binxin Zhu

    (New Energy Micro-grid Collaborative Innovation Centre of Hubei Province, China Three Gorges University, Yichang 443002, China)

Abstract

Studying the faster and more efficient method of solving the uncertain security-constrained unit commitment (SCUC) problem is an urgent need for the development of power systems under the background of large-scale wind power access and power dispatching. This study proposes an improved constrained order optimization (COO) algorithm to solve the uncertain SCUC problem. First, the data-driven discrete variable identification strategy is incorporated into the COO rough model, and then, the invalid security constraints identification strategy is incorporated into the COO accurate model. Finally, the improved COO algorithm combines the discrete variable identification with the invalid security constraint identification to make the uncertain SCUC decision. The results of the IEEE 118-bus test system showed that, compared with the traditional COO algorithm, the improved COO algorithm proposed has higher accuracy and better efficiency.

Suggested Citation

  • Junjie Jia & Nan Yang & Chao Xing & Haoze Chen & Songkai Liu & Yuehua Huang & Binxin Zhu, 2019. "An Improved Constrained Order Optimization Algorithm for Uncertain SCUC Problem Solving," Energies, MDPI, vol. 12(23), pages 1-19, November.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:23:p:4498-:d:291026
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    References listed on IDEAS

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    3. T. W. Edward Lau & Y. C. Ho, 1997. "Universal Alignment Probabilities and Subset Selection for Ordinal Optimization," Journal of Optimization Theory and Applications, Springer, vol. 93(3), pages 455-489, June.
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