Optimal allocation of battery energy storage system using whale optimization algorithm
Battery storage; Electric batteries; Battery energy storage systems; Firefly algorithms; Loss reduction; Meta-heuristic methods; Optimal allocation; Optimization algorithms; Overall system loss reduction; Performance; System loss; Whale optimization algorithm; Particle swarm optimization (PSO)
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Institute of Electrical and Electronics Engineers Inc.
2023
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| _version_ | 1833351454016929792 |
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| author | Wong L.A. Ramachandaramurthy V.K. |
| author2 | 57205119530 |
| author_facet | 57205119530 Wong L.A. Ramachandaramurthy V.K. |
| author_sort | Wong L.A. |
| building | UNITEN Library |
| collection | Institutional Repository |
| content_provider | Universiti Tenaga Nasional |
| content_source | UNITEN Institutional Repository |
| continent | Asia |
| country | Malaysia |
| description | Battery storage; Electric batteries; Battery energy storage systems; Firefly algorithms; Loss reduction; Meta-heuristic methods; Optimal allocation; Optimization algorithms; Overall system loss reduction; Performance; System loss; Whale optimization algorithm; Particle swarm optimization (PSO) |
| format | Conference Paper |
| id | my.uniten.dspace-25949 |
| institution | Universiti Tenaga Nasional |
| publishDate | 2023 |
| publisher | Institute of Electrical and Electronics Engineers Inc. |
| record_format | dspace |
| spelling | my.uniten.dspace-259492023-05-29T17:05:43Z Optimal allocation of battery energy storage system using whale optimization algorithm Wong L.A. Ramachandaramurthy V.K. 57205119530 6602912020 Battery storage; Electric batteries; Battery energy storage systems; Firefly algorithms; Loss reduction; Meta-heuristic methods; Optimal allocation; Optimization algorithms; Overall system loss reduction; Performance; System loss; Whale optimization algorithm; Particle swarm optimization (PSO) In this paper, a metaheuristic method is suggested to attain the optimal locations and sizing of the battery energy storage system (BESS), with the intention to decrease the overall system losses in a distribution system. To increase the reliability of the outcome, simultaneous optimization approach is employed, where the optimization problem is solved using Whale Optimization Algorithm (WOA). The hourly variation of photovoltaic (PV) generation and load profile for up to one week is considered in this work. The performance of WOA is validated with Particle Swarm Optimization (PSO) and Firefly Algorithm (FA). The optimization outcomes proved the ability of WOA in attaining the optimal BESS allocations for overall system losses reduction where the optimal solutions suggested by WOA has achieved the highest overall system losses reduction, followed by PSO while FA has the worst performance in this application. � 2021 IEEE. Final 2023-05-29T09:05:43Z 2023-05-29T09:05:43Z 2021 Conference Paper 10.1109/ICECCME52200.2021.9591039 2-s2.0-85119443208 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85119443208&doi=10.1109%2fICECCME52200.2021.9591039&partnerID=40&md5=ab26e9c0e118556afdc9f0f04bbb936e https://irepository.uniten.edu.my/handle/123456789/25949 Institute of Electrical and Electronics Engineers Inc. Scopus |
| spellingShingle | Wong L.A. Ramachandaramurthy V.K. Optimal allocation of battery energy storage system using whale optimization algorithm |
| title | Optimal allocation of battery energy storage system using whale optimization algorithm |
| title_full | Optimal allocation of battery energy storage system using whale optimization algorithm |
| title_fullStr | Optimal allocation of battery energy storage system using whale optimization algorithm |
| title_full_unstemmed | Optimal allocation of battery energy storage system using whale optimization algorithm |
| title_short | Optimal allocation of battery energy storage system using whale optimization algorithm |
| title_sort | optimal allocation of battery energy storage system using whale optimization algorithm |
| url_provider | http://dspace.uniten.edu.my/ |