Optimal placement and sizing of battery energy storage system for losses reduction using whale optimization algorithm
•Optimal allocation of battery energy storage system reduces the total system losses.•Different case studies with different number of storage were carried out.•Simultaneous BESS allocation optimization is better than the two steps optimization. This paper proposes an approach for optimal placement a...
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| Vydané v: | Journal of energy storage Ročník 26; s. 100892 |
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| Hlavní autori: | , , , , |
| Médium: | Journal Article |
| Jazyk: | English |
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Elsevier Ltd
01.12.2019
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| ISSN: | 2352-152X, 2352-1538 |
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| Abstract | •Optimal allocation of battery energy storage system reduces the total system losses.•Different case studies with different number of storage were carried out.•Simultaneous BESS allocation optimization is better than the two steps optimization.
This paper proposes an approach for optimal placement and sizing of battery energy storage system (BESS) to reduce the power losses in the distribution grid. A meta-heuristic optimization algorithm known as Whale Optimization Algorithm (WOA) is introduced to perform the optimization. In this paper, two different approaches are presented to achieve the optimal allocation of the BESS. The first approach is to obtain the optimal location and sizing in two steps while the second approach optimizes both location and sizing simultaneously. The performance of the proposed technique has been validated by comparing with two other algorithms namely firefly algorithm and particle swarm optimization. The results show that WOA has outstanding performance in attaining the optimal location and sizing of BESS in the distribution network for power losses reduction. |
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| AbstractList | •Optimal allocation of battery energy storage system reduces the total system losses.•Different case studies with different number of storage were carried out.•Simultaneous BESS allocation optimization is better than the two steps optimization.
This paper proposes an approach for optimal placement and sizing of battery energy storage system (BESS) to reduce the power losses in the distribution grid. A meta-heuristic optimization algorithm known as Whale Optimization Algorithm (WOA) is introduced to perform the optimization. In this paper, two different approaches are presented to achieve the optimal allocation of the BESS. The first approach is to obtain the optimal location and sizing in two steps while the second approach optimizes both location and sizing simultaneously. The performance of the proposed technique has been validated by comparing with two other algorithms namely firefly algorithm and particle swarm optimization. The results show that WOA has outstanding performance in attaining the optimal location and sizing of BESS in the distribution network for power losses reduction. |
| ArticleNumber | 100892 |
| Author | Sanjari, Mohammad Javad Walker, Sara L. Taylor, Phil Ramachandaramurthy, Vigna K. Wong, Ling Ai |
| Author_xml | – sequence: 1 givenname: Ling Ai surname: Wong fullname: Wong, Ling Ai email: ling.ai.wong@ucts.edu.my organization: Institute of Power Engineering, Department of Electrical Power Engineering, College of Engineering, Universiti Tenaga Nasional, Jalan IKRAM-UNITEN, 43000 Kajang, Selangor, Malaysia – sequence: 2 givenname: Vigna K. surname: Ramachandaramurthy fullname: Ramachandaramurthy, Vigna K. organization: Institute of Power Engineering, Department of Electrical Power Engineering, College of Engineering, Universiti Tenaga Nasional, Jalan IKRAM-UNITEN, 43000 Kajang, Selangor, Malaysia – sequence: 3 givenname: Sara L. surname: Walker fullname: Walker, Sara L. organization: School of Engineering, Newcastle University, Newcastle Upon Tyne, NE1 7RU, United Kingdom – sequence: 4 givenname: Phil surname: Taylor fullname: Taylor, Phil organization: School of Engineering, Newcastle University, Newcastle Upon Tyne, NE1 7RU, United Kingdom – sequence: 5 givenname: Mohammad Javad surname: Sanjari fullname: Sanjari, Mohammad Javad organization: School of Engineering, Griffith University, Gold Coast, QLD 4222, Australia |
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