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Optimal sizing of solar photovoltaics and battery storage for domestic prosumers using genetic algorithm

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dc.contributor.author Premadasa, PND
dc.contributor.author Silva, CMMRS
dc.contributor.author Chandima, DP
dc.contributor.author Karunadasa, JP
dc.contributor.editor Abeysooriya, R
dc.contributor.editor Adikariwattage, V
dc.contributor.editor Hemachandra, K
dc.date.accessioned 2024-03-21T08:13:00Z
dc.date.available 2024-03-21T08:13:00Z
dc.date.issued 2023-12-09
dc.identifier.citation P. N. D. Premadasa, C. M. M. R. S. Silva, D. P. Chandima and J. P. Karunadasa, "Optimal Sizing of Solar Photovoltaics and Battery Storage for Domestic Prosumers Using Genetic Algorithm," 2023 Moratuwa Engineering Research Conference (MERCon), Moratuwa, Sri Lanka, 2023, pp. 131-136, doi: 10.1109/MERCon60487.2023.10355510. en_US
dc.identifier.uri http://dl.lib.uom.lk/handle/123/22362
dc.description.abstract Recently, the number of prosumers is increasing significantly in the electrical system. Most prosumers use solar photovoltaics to generate electricity; some even use batteries to store excess energy. However, integrating solar photovoltaics with batteries increases the system costs. Therefore, optimal sizing of these storage systems and renewable generation is a critical requirement of the prosumers to reduce investment costs and increase system efficiency. Also, having the correct renewable generation and storage capacity sizes is crucial to profit from the system. This study presents an optimal sizing algorithm to size the solar photovoltaic system and battery storage system for domestic prosumers, giving the minimum cost using genetic algorithm. In the context of Sri Lanka, grid availability also uses as an input parameter to optimize the system capacities since the country had planned power outages continuously throughout a year. By contrast, the optimization results found that 14 solar panels with 8kWh battery capacity are sufficient for a load profile that has a peak demand of 4.5kW with a grid availability of 88.9%. Also, the optimized system has a 14-year payback period and a 6.8% of loss of load probability. With the proposed integrated system, power availability has been increased by 4.8%. en_US
dc.language.iso en en_US
dc.publisher IEEE en_US
dc.relation.uri https://ieeexplore.ieee.org/document/10355510/ en_US
dc.subject Solar photovoltaics en_US
dc.subject Battery storage en_US
dc.subject Prosumers en_US
dc.subject Optimal sizing en_US
dc.subject Genetic algorithm en_US
dc.title Optimal sizing of solar photovoltaics and battery storage for domestic prosumers using genetic algorithm en_US
dc.type Conference-Full-text en_US
dc.identifier.faculty Engineering en_US
dc.identifier.department Engineering Research Unit, University of Moratuwa en_US
dc.identifier.year 2023 en_US
dc.identifier.conference Moratuwa Engineering Research Conference 2023 en_US
dc.identifier.place Katubedda en_US
dc.identifier.pgnos pp. 131-136 en_US
dc.identifier.proceeding Proceedings of Moratuwa Engineering Research Conference 2023 en_US
dc.identifier.email dishanin@uom.lk en_US
dc.identifier.email silvacmmrs.20@uom.lk en_US
dc.identifier.email chandimadp@uom.lk en_US
dc.identifier.email karunadasaj@uom.lk en_US


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