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The Implementation of a New Optimization Method for Hydropower Generation and Multi-Reservoir Systems

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  • Abbas Moghani

    (Semnan University)

  • Hojat Karami

    (Semnan University)

Abstract

This research tries to find the best operation strategies for a reservoir system with the Flow Direction Algorithm (FDA), which was recently introduced. This study evaluates the implementation of the FDA, for the first time, for optimizing the hydropower operation of the Karun-4 reservoir in Iran for 106 months (from October 2010 to July 2019) and for the multi-reservoir systems for 12 months. Multi-Reservoir systems which are hypothetical 4 and 10-reservoir systems are studied to demonstrate the effectiveness and robustness of the algorithms. The results are compared to those of the three most commonly used evolutionary algorithms, namely the Particle Swarm Optimization Algorithm (PSO), the Weed Algorithm (WA), and the Genetic Algorithm (GA). The multi-reservoir results indicated that the absolute optimal solution was 308.292 in the four-reservoir benchmark system (FRBS) and 1194.441 in the ten-reservoir benchmark system (TRBS), and according to these results, FDA outperformed three other algorithms. In the Karun-4 reservoir, the best approach was chosen with the analytical hierarchy process (AHP) method, and according to the results, the FDA outperformed PSO, WA, and GA. The reliability percentage for FDA, PSO, WA, and GA was 95%, 86%, 78%, and 64%, respectively. The average optimal objective function value generated by FDA was 0.138, compared with PSO, WA, and GA, with the values of 0.322, 0.631, and 1.112, respectively, being better. The hydropower produced by FDA was more than three other algorithms in less time, with the lowest coefficient of variation value, which demonstrates the power of the FDA.

Suggested Citation

  • Abbas Moghani & Hojat Karami, 2024. "The Implementation of a New Optimization Method for Hydropower Generation and Multi-Reservoir Systems," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 38(5), pages 1711-1735, March.
    • Handle: RePEc:spr:waterr:v:38:y:2024:i:5:d:10.1007_s11269-024-03762-7
    DOI: 10.1007/s11269-024-03762-7
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    References listed on IDEAS

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    1. 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.
    2. 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.
    3. Mohammad Azizipour & Vahid Ghalenoei & M. H. Afshar & S. S. Solis, 2016. "Optimal Operation of Hydropower Reservoir Systems Using Weed Optimization Algorithm," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(11), pages 3995-4009, September.
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