Five different distributions and metaheuristics to model wind speed distribution

dc.authorscopusid57193868250
dc.authorwosidABG-8088-2020
dc.contributor.authorWadi, Mohammed
dc.contributor.authorWadi, Mohammed
dc.date.accessioned2022-03-04T19:12:32Z
dc.date.available2022-03-04T19:12:32Z
dc.date.issued2021
dc.departmentMühendislik ve Doğa Bilimleri Fakültesien_US
dc.description.abstractThis paper presents a comprehensive empirical study of five distribution functions to analyze wind energy potential: Rayleigh, Weibull, Gamma, Burr Type XII, and Generalized Extreme Value. In addition, two metaheuristics optimization methods, Grey Wolf optimization and Whale optimization algorithm, are utilized to determine the optimal parameter values of each distribution. Five error measures are investigated and compared to test the accuracy of the introduced distributions and optimization methods, such as mean absolute error, root mean square error, regression coefficient, correlation coefficient, and net fitness. The Catalca site in Istanbul, Turkey, was selected to be the case study to conduct this analysis. The obtained results confirm that all introduced distributions based on optimization methods efficiently model wind speed distribution in the selected site. Although Gamma distribution based on GWO and WOA outperformed other distributions for all datasets at all heights, it was the worst in terms of computation complexity. Rayleigh distribution occupied the latest rank, but it was the best in terms of computation complexity. MATLAB 2020b and Excel 365 were used to perform this study. © 2021. All Rights Reserved.en_US
dc.identifier.citationWadi, M.. (2021). Five different distributions and metaheuristics to model wind speed distribution. Journal of Thermal Engineering, 7(Supp 14), 1898–1920. https://doi.org/10.18186/thermal.1051262
dc.identifier.doi10.18186/THERMAL.1051262
dc.identifier.endpage1920en_US
dc.identifier.issn2148-7847
dc.identifier.issueSupplement14en_US
dc.identifier.orcid0000-0001-8928-3729
dc.identifier.scopus2-s2.0-85123750410en_US
dc.identifier.scopusqualityQ3
dc.identifier.startpage1898en_US
dc.identifier.trdizinid1172244
dc.identifier.urihttps://doi.org/10.18186/THERMAL.1051262
dc.identifier.urihttps://hdl.handle.net/20.500.12436/3237
dc.identifier.urihttps://search.trdizin.gov.tr/tr/yayin/detay/1172244
dc.identifier.volume7en_US
dc.identifier.wosWOS:000756697000005
dc.identifier.wosqualityN/Aen_US
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.indekslendigikaynakTR-Dizin
dc.institutionauthorWadi, Mohammed
dc.language.isoen
dc.publisherYildiz Technical Universityen_US
dc.relation.ispartofJournal of Thermal Engineeringen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectCumulative distribution function (CDF)en_US
dc.subjectGrey Wolf Optimization (GWO)en_US
dc.subjectInverse CDF (ICDF)en_US
dc.subjectProbability distribution function (PDF)en_US
dc.subjectStatistical distributionsen_US
dc.subjectWhale Optimization Algorithm (WOA)en_US
dc.subjectWind Energyen_US
dc.subjectWind Speeden_US
dc.titleFive different distributions and metaheuristics to model wind speed distributionen_US
dc.typeArticle
dspace.entity.typePublication
relation.isAuthorOfPublicatione57e2394-09f4-4128-bdb4-84c708867a9f
relation.isAuthorOfPublication.latestForDiscoverye57e2394-09f4-4128-bdb4-84c708867a9f

Dosyalar

Orijinal paket

Listeleniyor 1 - 1 / 1
Yükleniyor...
Küçük Resim
İsim:
10.18186-thermal.1051262-2167335.pdf
Boyut:
3.81 MB
Biçim:
Adobe Portable Document Format
Açıklama:
Makale dosyası / Article file