Multi-strategy Slime Mould Algorithm for hydropower multi-reservoir systems optimization
Article
Article Title | Multi-strategy Slime Mould Algorithm for hydropower multi-reservoir systems optimization |
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ERA Journal ID | 18062 |
Article Category | Article |
Authors | Ahmadianfar, Iman (Author), Noori, Ramzia Majeed (Author), Togun, Hussein (Author), Falah, Mayadah W. (Author), Homod, Raad Z. (Author), Fu, Minglei (Author), Halder, Bijay (Author), Deo, Ravinesh (Author) and Yaseen, Zaher Mundher (Author) |
Journal Title | Knowledge-Based Systems |
Journal Citation | 250, pp. 1-18 |
Article Number | 109048 |
Number of Pages | 18 |
Year | 2022 |
Publisher | Elsevier |
Place of Publication | Netherlands |
ISSN | 0950-7051 |
1872-7409 | |
Digital Object Identifier (DOI) | https://doi.org/10.1016/j.knosys.2022.109048 |
Web Address (URL) | https://www.sciencedirect.com/science/article/pii/S0950705122005135 |
Abstract | 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. |
Keywords | Optimization; Hydropower; Multi-reservoir; Operation; Slime Mould Algorithm; Multi-strategy |
Contains Sensitive Content | Does not contain sensitive content |
ANZSRC Field of Research 2020 | 460207. Modelling and simulation |
400803. Electrical energy generation (incl. renewables, excl. photovoltaics) | |
Public Notes | Files associated with this item cannot be displayed due to copyright restrictions. |
Byline Affiliations | Behbahan Khatam Alanbia University of Technology, Iran |
General Company of Electricity Transmission North Region, Iraq | |
University of Thi-Qar, Iraq | |
Al-Mustaqbal University College, Iraq | |
Basrah University for Oil and Gas, Iraq | |
Zhejiang University of Technology, China | |
Vidyasagar University, India | |
School of Mathematics, Physics and Computing | |
National University of Malaysia | |
Institution of Origin | University of Southern Queensland |
https://research.usq.edu.au/item/q760q/multi-strategy-slime-mould-algorithm-for-hydropower-multi-reservoir-systems-optimization
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