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

dc.contributor.authorPremadasa, PND
dc.contributor.authorSilva, CMMRS
dc.contributor.authorChandima, DP
dc.contributor.authorKarunadasa, JP
dc.contributor.editorAbeysooriya, R
dc.contributor.editorAdikariwattage, V
dc.contributor.editorHemachandra, K
dc.date.accessioned2024-03-21T08:13:00Z
dc.date.available2024-03-21T08:13:00Z
dc.date.issued2023-12-09
dc.description.abstractRecently, 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.identifier.citationP. 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.conferenceMoratuwa Engineering Research Conference 2023en_US
dc.identifier.departmentEngineering Research Unit, University of Moratuwaen_US
dc.identifier.emaildishanin@uom.lken_US
dc.identifier.emailsilvacmmrs.20@uom.lken_US
dc.identifier.emailchandimadp@uom.lken_US
dc.identifier.emailkarunadasaj@uom.lken_US
dc.identifier.facultyEngineeringen_US
dc.identifier.pgnospp. 131-136en_US
dc.identifier.placeKatubeddaen_US
dc.identifier.proceedingProceedings of Moratuwa Engineering Research Conference 2023en_US
dc.identifier.urihttp://dl.lib.uom.lk/handle/123/22362
dc.identifier.year2023en_US
dc.language.isoenen_US
dc.publisherIEEEen_US
dc.relation.urihttps://ieeexplore.ieee.org/document/10355510/en_US
dc.subjectSolar photovoltaicsen_US
dc.subjectBattery storageen_US
dc.subjectProsumersen_US
dc.subjectOptimal sizingen_US
dc.subjectGenetic algorithmen_US
dc.titleOptimal sizing of solar photovoltaics and battery storage for domestic prosumers using genetic algorithmen_US
dc.typeConference-Full-texten_US

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