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Large Scale Reservoirs System Operation Optimization: the Interior Search Algorithm (ISA) Approach

Author

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  • Mojtaba Moravej

    (University of Tehran)

  • Seyed-Mohammad Hosseini-Moghari

    (University of Tehran)

Abstract

Reservoirs are built to provide a powerful tool to control and manage surface water resources in order to cover inconsistency between water resources and demands. Due to finite available water and the increasing demands for water especially in arid and semi-arid regions like Iran, reservoirs must be optimally operated in order to use water in the most efficient way. This study applies the Interior Search Algorithm (ISA) to solve large scale reservoirs system operation optimization problems. The ISA is a meta-heuristic algorithm inspired from a systematic methodology of architecture process and mirror work utilized by Persian designers for decoration. Unlike other meta-heuristic algorithms, the ISA just have one parameter to tune which is a great advantage. In this study the parameter of the ISA tuned automatically using a linear equation. A real-world one-reservoir operation problem (i.e. Karun-4) and two large scale benchmark problems (i.e. four-reservoir and ten-reservoir operation problem) were employed to show the effectiveness of the ISA. The results shows the high ability of the ISA to solve reservoirs system operation problems as it achieved solutions 99.97, 99.99 and 99.95 % of global optimum for Karun-4 reservoir, four-reservoir and ten-reservoir system operation problems, respectively. These results are the best results reported so far in the studied problems. Comparing results of the ISA with those of non-linear programming (NLP), linear programming (LP), genetic algorithm (GA) and other meta-heuristic algorithms indicates fast convergence to global optimum. Considering the results, it can be stated that the ISA is a powerful tool to optimize complex large scale reservoir system operation problems.

Suggested Citation

  • Mojtaba Moravej & Seyed-Mohammad Hosseini-Moghari, 2016. "Large Scale Reservoirs System Operation Optimization: the Interior Search Algorithm (ISA) Approach," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(10), pages 3389-3407, August.
    • Handle: RePEc:spr:waterr:v:30:y:2016:i:10:d:10.1007_s11269-016-1358-y
    DOI: 10.1007/s11269-016-1358-y
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    2. Zhe Yang & Kan Yang & Hu Hu & Lyuwen Su, 2019. "The Cascade Reservoirs Multi-Objective Ecological Operation Optimization Considering Different Ecological Flow Demand," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 33(1), pages 207-228, January.
    3. Majid Mohammadi & Saeed Farzin & Sayed-Farhad Mousavi & Hojat Karami, 2019. "Investigation of a New Hybrid Optimization Algorithm Performance in the Optimal Operation of Multi-Reservoir Benchmark Systems," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 33(14), pages 4767-4782, November.
    4. Luckny Zephyr & Bernard F. Lamond & Pascal Lang, 2024. "Hybrid simplicial-randomized approximate stochastic dynamic programming for multireservoir optimization," Computational Management Science, Springer, vol. 21(1), pages 1-44, June.
    5. 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.

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