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Application Research of the Improved Overall Temporal and Spatial Economic Operation Model Based on Information Entropy in Large-Scale Hydropower Station

Author

Listed:
  • Liu Yang

    (Hohai University)

  • Kan Yang

    (Hohai University)

  • Lei Chen

    (Fujian Province Investigation Design and Research Institute of Water Conservancy and Hydropower)

Abstract

For the high dimensional and complex inner-plant economical operation problem of large hydropower station, an improved ant colony optimization with adaptive ability, inspiring ability and local search ability was proposed. Spatial optimal load distribution model and temporal unit commitment model was combined into an overall temporal and spatial economic operation model, in which an innovative ant colony model of multiple ant colonies, multiple outsets and multiple routes was adopted. Information entropy was applied to adjust the path selection strategy and pheromone updating strategy of ant colonies along with the change of its value during the iteration. Two inspiring factors were applied in the algorithm to guide the ant colonies to search for optimal paths in a more efficient and targeted way. Local search ability was guaranteed by local translation of unit start-stop points of the optimal solution in each iteration. In the optimal load distribution model, optimal distribution table was set in advance using dynamic programming, which only took account of the stable operation regions and avoided the cavitation and vibration areas for the security and stability of units. The proposed method is applied to the Three Gorges Hydroelectric plant. Compared with other methods under different water heads, this method shows optimized result under the premise of both calculation speed and stability.

Suggested Citation

  • Liu Yang & Kan Yang & Lei Chen, 2018. "Application Research of the Improved Overall Temporal and Spatial Economic Operation Model Based on Information Entropy in Large-Scale Hydropower Station," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 32(7), pages 2437-2456, May.
    • Handle: RePEc:spr:waterr:v:32:y:2018:i:7:d:10.1007_s11269-018-1938-0
    DOI: 10.1007/s11269-018-1938-0
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    References listed on IDEAS

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    1. Zhang, Jingrui & Tang, Qinghui & Chen, Yalin & Lin, Shuang, 2016. "A hybrid particle swarm optimization with small population size to solve the optimal short-term hydro-thermal unit commitment problem," Energy, Elsevier, vol. 109(C), pages 765-780.
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    Cited by:

    1. Yang, Zhe & Wang, Yufeng & Yang, Kan, 2022. "The stochastic short-term hydropower generation scheduling considering uncertainty in load output forecasts," Energy, Elsevier, vol. 241(C).
    2. Kun Yang & Kan Yang, 2022. "Improved Whale Algorithm for Economic Load Dispatch Problem in Hydropower Plants and Comprehensive Performance Evaluation," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(15), pages 5823-5838, December.
    3. Wu, Xinyu & Wu, Yiyang & Cheng, Xilong & Cheng, Chuntian & Li, Zehong & Wu, Yongqi, 2023. "A mixed-integer linear programming model for hydro unit commitment considering operation constraint priorities," Renewable Energy, Elsevier, vol. 204(C), pages 507-520.

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