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              <text>Coyote optimization algorithm for optimal allocation of interline Photovoltaic battery storage system in islanded electrical distribution network considering EV load penetration</text>
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              <text>Battery energy storage system; Coyote optimization algorithm; Electric vehicle load; Islanding operation; Multi-objective optimization; Solar photovoltaic system</text>
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              <text>In current times, there is a need to do power system planning to endure situations of any kind. An islanding operation is one such unavoidable situation that may be required in many cases for both technical and economic reasons. First and foremost, this paper focuses on the determination of the best allotment of Interline-Photovoltaic (I-PV) system as per Electric Vehicle (EV) load penetration in the network. With different operational constraints, a multi-objective optimization using real power loss and voltage deviation index is formulated and solved using the Coyote Optimization Algorithm (COA).The paper highlights the computational efficiency of COA with Particle Swarm Optimization (PSO) and Grey Wolf Optimizer (GWO), in addition to various literary works, and the results suggest the superiority of COA by its global optima. The required battery energy storage system (BESS) capacity for supplying an islanded network's entire load demand for a day is determined in the second stage. The simulations were carried out on the IEEE 33-bus electrical distribution network (EDN) contemplating different levels of EV load penetration. The proposed methodology results have proved that the required energy is provided by optimal I-PV-BESS backup for a daylong islanding operation and its adaptability for practical situations.  2021 Elsevier Ltd</text>
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              <text>Janamala V.; Sreenivasulu Reddy D.</text>
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              <text>Journal of Energy Storage, Vol-41</text>
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              <text>Elsevier Ltd</text>
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              <text>2021-01-01</text>
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              <text>&lt;a href="https://doi.org/10.1016/j.est.2021.102981" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1016/j.est.2021.102981&lt;/a&gt;
&lt;br /&gt;&lt;br /&gt;&lt;a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85111473997&amp;amp;doi=10.1016%2Fj.est.2021.102981&amp;amp;partnerID=40&amp;amp;md5=5aec6b1cd3fbdb6c2e926cab51d4e59b" target="_blank" rel="noreferrer noopener"&gt;https://www.scopus.com/inward/record.uri?eid=2-s2.0-85111473997&amp;amp;doi=10.1016%2fj.est.2021.102981&amp;amp;partnerID=40&amp;amp;md5=5aec6b1cd3fbdb6c2e926cab51d4e59b&lt;/a&gt;</text>
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              <text>ISSN: 2352152X</text>
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              <text>English</text>
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              <text>Janamala V., Dept. of Electrical and Electronics Engineering, School of Engineering and Technology, CHRIST (Deemed to be University), Bangalore, 560 074, Karnataka, India; Sreenivasulu Reddy D., Dept. of Electrical and Electronics Engineering, School of Engineering and Technology, CHRIST (Deemed to be University), Bangalore, 560 074, Karnataka, India</text>
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