Robust Diversity-based Sine-Cosine Algorithm for Optimizing Hydropower Multi-reservoir Systems

Hydropower energy generation depends on the available water resources. Therefore, planning and operation of the water resource systems are paramount tasks for energy management. Since reservoirs are one of the important components of water resources systems, extracting optimal operating policies for...

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Published inWater resources management Vol. 35; no. 11; pp. 3513 - 3538
Main Authors Ahmadianfar, Iman, Noshadian, Saeed, Elagib, Nadir Ahmed, Salarijazi, Meysam
Format Journal Article
LanguageEnglish
Published Dordrecht Springer Netherlands 01.09.2021
Springer Nature B.V
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ISSN0920-4741
1573-1650
DOI10.1007/s11269-021-02903-6

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Summary:Hydropower energy generation depends on the available water resources. Therefore, planning and operation of the water resource systems are paramount tasks for energy management. Since reservoirs are one of the important components of water resources systems, extracting optimal operating policies for proper management of energy generated from these systems is an imperative step. Optimizing reservoir system operation (ORSO) is a non-linear, large-scale, and non-convex problem with a large number of constraints and decision variables. To solve ORSO problem effectively, a robust diversity-based, sine-cosine algorithm (RDB-SCA) is developed in the present study by introducing several strategies to balance the global exploration and local exploitation ability and to achieve accurate and reliable solutions. An efficient linear operation rule is coupled with the RDB-SCA to maximize the energy generation. The proposed method is then applied to a real-world, multi-reservoir system to extract optimal operational policies and, consequently, maximize the energy production. It is shown that the RDB-SCA is able to generate 24, 14, and 6% more energy than the original SCA, respectively for 2-, 3-, and 4-reservoir systems. The present findings are useful to suggest guidelines for efficient operation of hydropower multi-reservoir systems. This paper is supported by  https://imanahmadianfar.com/codes .
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ISSN:0920-4741
1573-1650
DOI:10.1007/s11269-021-02903-6