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Improved Whale Algorithm for Economic Load Dispatch Problem in Hydropower Plants and Comprehensive Performance Evaluation

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  • Kun Yang

    (Hohai University)

  • Kan Yang

    (Hohai University)

Abstract

A novel method for economic load dispatch problem (ELDP) based on improved whale optimization algorithm(IWOA) is presented, and the optimization performance of IWOA in ELDP was evaluated comprehensively. The search mechanism is modified to improve the ability of the algorithm to jump out of the local optimal. The adaptive nonlinear inertia weight is introduced to improve the convergence speed of the algorithm. A limited mutation mechanism is proposed to improve the convergence of the algorithm. The evaluation indicator of calculation time and calculation accuracy was established. Taking 26 units of the Three Gorges Hydropower Station as an example, limited adaptive genetic aigorithm (LAGA), particle swarm optimization (PSO), whale optimization algorithm (WOA) and improved whale optimization algorithm (IWOA) were used to solve ELDP. The result shows that IWOA is superior to other algorithms in calculation results of various heads and loads. The calculation accuracy of IWOA was better than WOA when the number of units turned on was more than 6. The analysis results of IWOA and DP show that the calculation time of IWOA is better than that of DP when the number of units turned on is more than 6. The IWOA and the evaluation indicators proposed in this paper provide a new way for solving ELDP of large hydropower stations.

Suggested Citation

  • 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.
    • Handle: RePEc:spr:waterr:v:36:y:2022:i:15:d:10.1007_s11269-022-03302-1
    DOI: 10.1007/s11269-022-03302-1
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    References listed on IDEAS

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    1. Alireza Amani & Hosein Alizadeh, 2021. "Solving Hydropower Unit Commitment Problem Using a Novel Sequential Mixed Integer Linear Programming Approach," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 35(6), pages 1711-1729, April.
    2. McLarty, Dustin & Panossian, Nadia & Jabbari, Faryar & Traverso, Alberto, 2019. "Dynamic economic dispatch using complementary quadratic programming," Energy, Elsevier, vol. 166(C), pages 755-764.
    3. Kun Yang & Kan Yang, 2021. "Short-Term Hydro Generation Scheduling of the Three Gorges Hydropower Station Using Improver Binary-coded Whale Optimization Algorithm," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 35(11), pages 3771-3790, September.
    4. 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.
    5. Nemati, Mohsen & Braun, Martin & Tenbohlen, Stefan, 2018. "Optimization of unit commitment and economic dispatch in microgrids based on genetic algorithm and mixed integer linear programming," Applied Energy, Elsevier, vol. 210(C), pages 944-963.
    6. Chang, Jianxia & Li, Yunyun & Yuan, Meng & Wang, Yimin, 2017. "Efficiency evaluation of hydropower station operation: A case study of Longyangxia station in the Yellow River, China," Energy, Elsevier, vol. 135(C), pages 23-31.
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    1. Li, Xudong & Yang, Weijia & Liao, Yiwen & Zhang, Shushu & Zheng, Yang & Zhao, Zhigao & Tang, Maojia & Cheng, Yongguang & Liu, Pan, 2024. "Short-term risk-management for hydro-wind-solar hybrid energy system considering hydropower part-load operating characteristics," Applied Energy, Elsevier, vol. 360(C).

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