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Optimizing Multiple Linear Rules for Multi-Reservoir Hydropower Systems Using an Optimization Method with an Adaptation Strategy

Author

Listed:
  • Iman Ahmadianfar

    (Behbahan Khatam Alanbia University of Technology)

  • Omid Bozorg-Haddad

    (University of Tehran)

  • Xuefeng Chu

    (North Dakota State University)

Abstract

Water resources crisis has a significant impact on hydropower energy production, which highlights the importance of water resources management. Reservoirs are effective and powerful systems to manage water resources. Due to the growing water demands and the limited water resources, optimizing these systems to maximize the production of hydropower energy is an essential task. In this study, an effective differential evolution (DE) algorithm with mutation strategy adaptation (MSA-DE) is developed to promote the local and global search capabilities in a feasible domain. In addition, an elitist strategy is applied to escape local optimum trap. In the present study, the MSA-DE algorithm was applied to optimize the multiple linear rules for two multi-reservoir operation systems (3- and 4-reservoir systems) in Iran. In the 3-reservoir system, the best objective function value in 10 runs was 123.57 for the MSA-DE, while the corresponding values for the DE, artificial bee colony (ABC), and genetic algorithm (GA) were 126.42, 147.38, and 126.68, respectively. For the 4-reservoir system, the best objective function values for the MSA-DE, DE, ABC, and GA were 130.50, 159.75, 174.41, and 140.63, respectively. The results demonstrated that the MSA-DE algorithm can be used to derive optimal operating rules for multi-reservoir systems by enhancing appropriate solutions, while it still preserves the accuracy and efficiency of the solutions.

Suggested Citation

  • Iman Ahmadianfar & Omid Bozorg-Haddad & Xuefeng Chu, 2019. "Optimizing Multiple Linear Rules for Multi-Reservoir Hydropower Systems Using an Optimization Method with an Adaptation Strategy," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 33(12), pages 4265-4286, September.
    • Handle: RePEc:spr:waterr:v:33:y:2019:i:12:d:10.1007_s11269-019-02364-y
    DOI: 10.1007/s11269-019-02364-y
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    References listed on IDEAS

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    2. Kobra Rahmati & Parisa-Sadat Ashofteh & Hugo A. Loáiciga, 2021. "Application of the Grasshopper Optimization Algorithm (GOA) to the Optimal Operation of Hydropower Reservoir Systems Under Climate Change," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 35(13), pages 4325-4348, October.
    3. Inkyung Min & Nakyung Lee & Sanha Kim & Yelim Bang & Juyeon Jang & Kichul Jung & Daeryong Park, 2024. "An Improved Aggregation–Decomposition Optimization Approach for Ecological Flow Supply in Parallel Reservoir Systems," Sustainability, MDPI, vol. 16(17), pages 1-22, August.
    4. Xuan Wang & Wenchong Tian & Zhenliang Liao, 2021. "Offline Optimization of Sluice Control Rules in the Urban Water System for Flooding Mitigation," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 35(3), pages 949-962, February.

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