Multi-strategy Slime Mould Algorithm for hydropower multi-reservoir systems optimization

• Published in: Knowledge-based systems Vol. 250; p. 109048
• Main Authors: Ahmadianfar, Iman, Noori, Ramzia Majeed, Togun, Hussein, Falah, Mayadah W., Homod, Raad Z., Fu, Minglei, Halder, Bijay, Deo, Ravinesh, Yaseen, Zaher Mundher
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 17.08.2022
• Subjects: Hydropower; Multi-reservoir; Multi-strategy; Operation; Optimization; Slime Mould Algorithm; Multi-reservoir; Hydropower; Slime Mould Algorithm; Operation; Optimization; Multi-strategy
• ISSN: 0950-7051; 1872-7409
• DOI: 10.1016/j.knosys.2022.109048

The challenge to determine the best policies for hydropower multiple reservoir systems is a high-dimensional and nonlinear problem, making it challenging to attain a global solution. To efficiently optimize such a complicated solution, the creation of a high-precision optimization algorithm is critical. Hence, this research proposes a Multi-strategy Slime Mould Algorithm (MSMA) to determine the optimal operating rules for a complicated hydropower multiple reservoir prediction problem. The MSMA system proposed employs an effective wrap food mechanism to strengthen local and global capability; an enhanced solution quality (ESQ) to promote solution quality; and the interior-point method to implement an influential exploitation mechanism. The numerical testing of 23 test functions demonstrates the efficiency of the MSMA algorithm in solving global optimization issues. The newly developed method is then used to optimize the operation of a complex eight-reservoir hydropower system, with the proposed MSMA approach resulting in ∼0.999% of an ideal global solution, according to the optimal findings. The results of the multi-reservoir system show that proposed MSMA method was able to generate about 16.6% more power than the SMA. Consequently, the recommended method outperforms the other well-known optimization methods for maximizing power in the multi-reservoir system. Finally, this study also provides a useful tool for optimizing the complicated hydropower multiple reservoir problems.