Modified grey wolf optimizer based MPPT design and experimentally performance evaluations for wind energy systems*

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dc.contributor.authorYazici, Irfan
dc.contributor.authorYaylaci, Ersagun Kuersat
dc.date.accessioned2024-09-29T15:57:37Z
dc.date.available2024-09-29T15:57:37Z
dc.date.issued2023
dc.departmentKarabük Üniversitesien_US
dc.description.abstractThe method that aims to operate the wind energy system (WES) at the maximum power point (MPP) is called the maximum power point tracking (MPPT) method in the literature. The grey wolf optimization (GWO) is one of the newest population-based meta-heuristic methods, and its performance as an MPPT algorithm in WESs has not been extensively studied yet. In this study, the standard GWO algorithm has been modified considering the requirements of WES, so that the system can reach the MPP quickly and stably, thereby improving the system's efficiency. Moreover, the performance of the proposed method is examined comparatively with the well-known MPPT methods via simulation and experimental studies for many possible scenarios. It is demonstrated that the proposed modified GWO (MGWO) performance is better than the classic and modified perturb and observe methods. The results have also been compared with the Fibonacci Search (FS) and Golden Section (GS) Search-based MPPT algorithms newly presented in the literature for WES. Although the results of FS, GS, and MGWO-based MPPT algorithms are very close to each other, it has been observed that FS has a slightly better performance.en_US
dc.description.sponsorshipScientific and Technological Research Council of Turkey (TUBIdot;TAK) [119E284]en_US
dc.description.sponsorshipThis research was funded by The Scientific and Technological Research Council of Turkey (TUBITAK) through a research grant account number 119E284.Also, the authors are so grateful to Bugra Ocalan and Senol Sayan from Iletken Enerji, Kocaeli, Turkiye for sharing the real wind speed data to do academic research.en_US
dc.identifier.doi10.1016/j.jestch.2023.101520
dc.identifier.issn2215-0986
dc.identifier.scopus2-s2.0-85169814684en_US
dc.identifier.scopusqualityQ1en_US
dc.identifier.urihttps://doi.org/10.1016/j.jestch.2023.101520
dc.identifier.urihttps://hdl.handle.net/20.500.14619/4919
dc.identifier.volume46en_US
dc.identifier.wosWOS:001074195400001en_US
dc.identifier.wosqualityQ1en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherElsevier - Division Reed Elsevier India Pvt Ltden_US
dc.relation.ispartofEngineering Science and Technology-An International Journal-Jestechen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectWind power systemsen_US
dc.subjectMaximum power point trackingen_US
dc.subjectGrey wolf optimizeren_US
dc.titleModified grey wolf optimizer based MPPT design and experimentally performance evaluations for wind energy systems*en_US
dc.typeArticleen_US

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