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Generation of Clean Hydropower Energy in Multi-Reservoir Systems Based on a New Evolutionary Algorithm

Author

Listed:
  • Mojgan Dianatikhah

    (Semnan University)

  • Hojat Karami

    (Semnan University)

  • Khosrow Hosseini

    (Semnan University)

Abstract

Lingering droughts and shortage of water sources signify the importance of optimal utilization of water reservoirs such as multi-reservoir systems. These systems could be employed not only as a storage system to manage the water utilization but also as a power generation system. To rise the generated power besides the management of water utilization, an optimization algorithm should be used. In this study, the kidney algorithm in three different scenarios, namely the wet, normal, and dry years is employed to fulfill such an engineering operation in a four-reservoir system in China. Simulations show well compatibility of the water level inside the reservoir with real statistical indices in terms of RMSE and MAE. Results also reveal that using the kidney algorithm not only reduces the required calculation but also increases the convergence pace with respect to other algorithms that have been used (bat, shark, abundance of particles, and genetic algorithms). Moreover, it increases the amount of the generated energy by a factor of 2.2–3.2 with respect to the aforementioned algorithms. Results indicate the capability of the kidney algorithm in the management of water sources and engineering operations.

Suggested Citation

  • Mojgan Dianatikhah & Hojat Karami & Khosrow Hosseini, 2020. "Generation of Clean Hydropower Energy in Multi-Reservoir Systems Based on a New Evolutionary Algorithm," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 34(3), pages 1247-1264, February.
    • Handle: RePEc:spr:waterr:v:34:y:2020:i:3:d:10.1007_s11269-020-02498-4
    DOI: 10.1007/s11269-020-02498-4
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    References listed on IDEAS

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    1. Bo Ming & Pan Liu & Tao Bai & Rouxin Tang & Maoyuan Feng, 2017. "Improving Optimization Efficiency for Reservoir Operation Using a Search Space Reduction Method," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 31(4), pages 1173-1190, March.
    2. Bo Ming & Jian-xia Chang & Qiang Huang & Yi-min Wang & Sheng-zhi Huang, 2015. "Optimal Operation of Multi-Reservoir System Based-On Cuckoo Search Algorithm," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(15), pages 5671-5687, December.
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    Cited by:

    1. Rahim Zahedi & Reza Eskandarpanah & Mohammadhossein Akbari & Nima Rezaei & Paniz Mazloumin & Omid Noudeh Farahani, 2022. "Development of a New Simulation Model for the Reservoir Hydropower Generation," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(7), pages 2241-2256, May.
    2. Tianwei Mu & Yaqi Li & Ziyi Li & Luyue Wang & Haoqiang Tan & Chengzhi Zheng, 2021. "Improved Network Reliability Optimization Model with Head Loss for Water Distribution System," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 35(7), pages 2101-2114, May.

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