Experimental analysis and dynamic modeling of a photovoltaic module with porous fins

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dc.authoridBAYRAK, FATIH/0000-0003-3715-6458
dc.authoridSelimefendigil, Fatih/0000-0002-5453-2091
dc.contributor.authorSelimefendigil, Fatih
dc.contributor.authorBayrak, Fatih
dc.contributor.authorOztop, Hakan F.
dc.date.accessioned2024-12-24T19:27:34Z
dc.date.available2024-12-24T19:27:34Z
dc.date.issued2018
dc.departmentSiirt Üniversitesi
dc.description.abstractIn this study, experimental analysis and performance predictions of solar photovoltaic (PV) module equipped with porous fins were performed. The experimental setup was tested in Technology Faculty of Firat University, Elazig of Turkey which is located at 36 and 42 North latitudes. The PV module was oriented facing south and tilted to an angle of 36 with respect to the horizontal in order to maximize the solar radiation incident on the glass cover. Experimental analysis was conducted for configurations where PV module is equipped with porous metal foams. A multi-input multi-output dynamic system based on artificial neural networks was obtained for the PV configuration with and without fin by using the measured data (ambient temperature, PV panels back surface temperatures, current, voltage, radiation and wind velocity) from the experimental test rig. It was observed that adding porous fins to the PV module results in performance enhancements. The developed mathematical model based on dynamic neural networks can be used for further development and performance predictions of these systems. (C) 2018 Elsevier Ltd. All rights reserved.
dc.description.sponsorshipScientific and Technological Research Council of Turkey (TUBITAK) [215M892]
dc.description.sponsorshipThe authors gratefully acknowledge the financial support provided by the Scientific and Technological Research Council of Turkey (TUBITAK) under the project no 215M892.
dc.identifier.doi10.1016/j.renene.2018.02.002
dc.identifier.endpage205
dc.identifier.issn0960-1481
dc.identifier.scopus2-s2.0-85042631581
dc.identifier.scopusqualityQ1
dc.identifier.startpage193
dc.identifier.urihttps://doi.org/10.1016/j.renene.2018.02.002
dc.identifier.urihttps://hdl.handle.net/20.500.12604/6707
dc.identifier.volume125
dc.identifier.wosWOS:000433648500017
dc.identifier.wosqualityQ1
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherPergamon-Elsevier Science Ltd
dc.relation.ispartofRenewable Energy
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzKA_20241222
dc.subjectPV module
dc.subjectPerformance predictions
dc.subjectSolar
dc.subjectArtificial neural networks
dc.titleExperimental analysis and dynamic modeling of a photovoltaic module with porous fins
dc.typeArticle

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