Grey wolf optimization for optimum sizing and controlling of a PV/WT/BM hybrid energy system considering TNPC, LPSP, and LCOE concepts

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dc.authoridGUNESER, Muhammet Tahir/0000-0003-3502-2034
dc.authoridKayabasi, Erhan/0000-0002-3603-6211
dc.contributor.authorTabak, Abdulsamed
dc.contributor.authorKayabasi, Erhan
dc.contributor.authorGuneser, Muhammet Tahir
dc.contributor.authorOzkaymak, Mehmet
dc.date.accessioned2024-09-29T16:02:57Z
dc.date.available2024-09-29T16:02:57Z
dc.date.issued2022
dc.departmentKarabük Üniversitesien_US
dc.description.abstractIn this study, energy demand of a faculty was aimed to supply with a hybrid energy system (HES) consisting of photovoltaic (PV) panels, wind turbine (WT) and bomass (BM) system with optimum power usage distribution and sized to reach a lowest cost and a reliable system. In this optimization, total net present cost (TNPC) for economic analysis, loss of power supply probability (LPSP) for reliability, and localized cost of energy (LCOE) for determining the unit energy cost were considered and an effective control algorithm was developed to decide the power source for improving system reliability. We used genetic algorithm (GA) and simulated annealing (SA), which are commonly used in the literature. On the other hand, we utilized the Grey Wolf Optimizer (GWO), which was recently found out and inspired by the hierarchy and hunting instincts of grey wolves. The results of GWO algorithm were also compared with GA and SA and confirmed that GWO is satisfying. GWO achieved better results to solve problems by setting LPSP to both 0.02 and 0.01 upper limits. When LPSP set to 0.02 maximum point, GWO suggested PV system at 86.39 kW power and BG at 50 kW power. Consequently, the energy requirement of a faculty was supplied by an optimized and designed PV/WT/BM HES. In addition, by the installation of optimized system, 144.29 tons of CO2 emissions per year will be reduced.en_US
dc.identifier.doi10.1080/15567036.2019.1668880
dc.identifier.endpage1528en_US
dc.identifier.issn1556-7036
dc.identifier.issn1556-7230
dc.identifier.issue1en_US
dc.identifier.scopus2-s2.0-85073920040en_US
dc.identifier.scopusqualityQ2en_US
dc.identifier.startpage1508en_US
dc.identifier.urihttps://doi.org/10.1080/15567036.2019.1668880
dc.identifier.urihttps://hdl.handle.net/20.500.14619/5810
dc.identifier.volume44en_US
dc.identifier.wosWOS:000488131000001en_US
dc.identifier.wosqualityQ3en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherTaylor & Francis Incen_US
dc.relation.ispartofEnergy Sources Part A-Recovery Utilization and Environmental Effectsen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectGenetic algorithmen_US
dc.subjectGrey Wolf Optimizeren_US
dc.subjecthybrid energy optimizationen_US
dc.subjectloss of power supply probabilityen_US
dc.subjectsimulated annealingen_US
dc.subjecttotal net present costen_US
dc.titleGrey wolf optimization for optimum sizing and controlling of a PV/WT/BM hybrid energy system considering TNPC, LPSP, and LCOE conceptsen_US
dc.typeArticleen_US

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