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Application of Multi-Strategy Based Improved DBO Algorithm in Optimal Scheduling of Reservoir Groups

Author

Listed:
  • Ji He

    (North China University of Water Resources and Electric Power)

  • Wen Guo

    (North China University of Water Resources and Electric Power)

  • Songlin Wang

    (North China University of Water Resources and Electric Power)

  • Haitao Chen

    (North China University of Water Resources and Electric Power)

  • Xiaoqi Guo

    (North China University of Water Resources and Electric Power)

  • Shumin Li

    (North China University of Water Resources and Electric Power)

Abstract

Aiming at the problems of high dimensionality, multi-constraint, multi-phase, non-linearity, and the fact that the established model is not easy to solve for the optimal scheduling of reservoir group flood control, this paper improved the dung beetle optimization algorithm by adopting a variety of strategies, proposes a new intelligent optimization algorithm, the multi-strategy improved dung beetle algorithm (MIDBO), and firstly applied it to the optimal scheduling of flood control in reservoir groups. In addition, this study analyzed and contrasted the MIDBO algorithm's calculation results with the examples of the particle swarm and dung beetle optimization algorithms in relation to the reservoir cluster in the middle and lower sections of the Yellow River. And the peak reduction rates of these algorithms are 52.82%, 51.48%, and 50.25% in turn. The outcomes demonstrate that the MIDBO algorithm has strong performance, fast optimization efficiency, obvious peak reduction effect, and is a feasible method to solve the optimization problem of reservoir flood control and scheduling.

Suggested Citation

  • Ji He & Wen Guo & Songlin Wang & Haitao Chen & Xiaoqi Guo & Shumin Li, 2024. "Application of Multi-Strategy Based Improved DBO Algorithm in Optimal Scheduling of Reservoir Groups," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 38(6), pages 1883-1901, April.
    • Handle: RePEc:spr:waterr:v:38:y:2024:i:6:d:10.1007_s11269-023-03656-0
    DOI: 10.1007/s11269-023-03656-0
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    References listed on IDEAS

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    1. Saad Dahmani & Djilali Yebdri, 2020. "Hybrid Algorithm of Particle Swarm Optimization and Grey Wolf Optimizer for Reservoir Operation Management," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 34(15), pages 4545-4560, December.
    2. Fuxin Chai & Feng Peng & Hongping Zhang & Wenbin Zang, 2023. "Stable Improved Dynamic Programming Method: An Efficient and Accurate Method for Optimization of Reservoir Flood Control Operation," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 37(14), pages 5635-5654, November.
    3. Chang Jian-Xia & Huang Qiang & Wang Yi-min, 2005. "Genetic Algorithms for Optimal Reservoir Dispatching," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 19(4), pages 321-331, August.
    4. He, Zhongzheng & Wang, Chao & Wang, Yongqiang & Wei, Bowen & Zhou, Jianzhong & Zhang, Hairong & Qin, Hui, 2021. "Dynamic programming with successive approximation and relaxation strategy for long-term joint power generation scheduling of large-scale hydropower station group," Energy, Elsevier, vol. 222(C).
    5. Hai-tao Chen & Wen-chuan Wang & Kwok-wing Chau & Lei Xu & Ji He, 2021. "Flood Control Operation of Reservoir Group Using Yin-Yang Firefly Algorithm," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 35(15), pages 5325-5345, December.
    6. Ji He & Xiaoqi Guo & Haitao Chen & Fuxin Chai & Shengming Liu & Hongping Zhang & Wenbin Zang & Songlin Wang, 2023. "Application of HSMAAOA Algorithm in Flood Control Optimal Operation of Reservoir Groups," Sustainability, MDPI, vol. 15(2), pages 1-16, January.
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    Cited by:

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    2. Guangyun Cui & Zhen Qi & Huaqing Zhao & Ranhang Zhao & Haofang Wang & Jiaxing Zhao, 2025. "Application of F-HGAPSO Algorithm in Reservoir Flood Control Optimal Operation," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 39(4), pages 1763-1782, March.

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