Multi-Objective Operation of PV-ESU Powered EV Charging Station

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dc.contributor.authorTutkun, Nedim
dc.contributor.authorZulkifli, Shamsul A.
dc.contributor.authorŞimşir, Mehmet
dc.date.accessioned2024-10-12T19:47:12Z
dc.date.available2024-10-12T19:47:12Z
dc.date.issued2024
dc.departmentİstanbul Ticaret Üniversitesien_US
dc.descriptionBeijing CAS Industrial Energy and Environment Technology Institute (BIEET); IEEE; University of Electronic Science and Technology of China (UESTC)en_US
dc.description7th Asia Conference on Energy and Electrical Engineering, ACEEE 2024 -- 20 July 2024 through 22 July 2024 -- Chengdu -- 202296en_US
dc.description.abstractRecently electric vehicles (EV s) have been popular choice in many countries due to low carbon emission and less operation cost. The rapid increase in EV s inevitably increases the number of charging stations used to charge them, and this naturally leads to more power demand at certain times of the day. It is also apparent that the increase in energy demand leads to an increase in electricity prices, as well as an increase in power loss in transmission lines. This may reduce the current aura of EV s, as higher electricity prices mean more expensive charging costs. Therefore, creating more competitive conditions at existing charging stations for lower charging costs is essential for a sustainable future. In this study, the primary objective is to reduce the charging cost by integrating a 20-kWp photovoltaic (PV) array and a 20-kWh energy storage unit (ESU) into an existing charging station fed from the grid and considering the overload of the grid and user charging preference. This multi-objective problem is solved for optimal daily cost using the binari-coded genetic algorithm (BCGA). The results show that proposed optimization model worked well, and the charging cost decreased depending on user preferences. © 2024 IEEE.en_US
dc.description.sponsorshipIstanbul Ticaret University; Board of Trustees, (ACEEE 2024)en_US
dc.identifier.doi10.1109/ACEEE62329.2024.10651779
dc.identifier.endpage118en_US
dc.identifier.isbn979-835035024-1
dc.identifier.scopus2-s2.0-85203815030en_US
dc.identifier.scopusqualityN/Aen_US
dc.identifier.startpage114en_US
dc.identifier.urihttps://doi.org/10.1109/ACEEE62329.2024.10651779
dc.identifier.urihttps://hdl.handle.net/11467/8802
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherInstitute of Electrical and Electronics Engineers Inc.en_US
dc.relation.ispartof2024 7th Asia Conference on Energy and Electrical Engineering, ACEEE 2024en_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.snmzScopus_20241012en_US
dc.subjectcharging costen_US
dc.subjectElectric vehiclesen_US
dc.subjectmetaheuristic techniquesen_US
dc.subjectphotovoltaicen_US
dc.subjectuser comforten_US
dc.titleMulti-Objective Operation of PV-ESU Powered EV Charging Stationen_US
dc.typeConference Objecten_US

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