Artificial neural network modelling and experimental verification of the operating current of mono-crystalline photovoltaic modules

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dc.authorid0000-0003-1559-7383
dc.contributor.authorÇelik, Ali Naci
dc.date.accessioned2021-06-23T19:27:40Z
dc.date.available2021-06-23T19:27:40Z
dc.date.issued2011
dc.departmentBAİBÜ, Mühendislik Fakültesi, Makine Mühendisliği Bölümüen_US
dc.description.abstractThis article presents the artificial neural network modelling of the operating current of a 120 Wp of mono-crystalline photovoltaic module. As an alternative method to analytical modelling approaches, this study uses the advantages of neural networks such as no required knowledge of internal system parameters, less computational effort and a compact solution for multivariable problems. Generalised regression neural network model is used in the present article to predict the operating current of the photovoltaic module. To show its merit, the current predicted from the artificial neural network modelling is compared to that from the analytical model. The five-parameter analytical model is drawn from the equivalent electrical circuit that includes light-generated current, diode reverse saturation current, and series and shunt resistances. The operating current predicted from both the neural and analytical models are compared to the measured current. Results have shown that the artificial neural network modelling provides a better prediction of the current than the five-parameter analytical model. (C) 2011 Elsevier Ltd. All rights reserved.en_US
dc.identifier.doi10.1016/j.solener.2011.07.009
dc.identifier.endpage2517en_US
dc.identifier.issn0038-092X
dc.identifier.issue10en_US
dc.identifier.scopus2-s2.0-80052289721en_US
dc.identifier.scopusqualityQ1en_US
dc.identifier.startpage2507en_US
dc.identifier.urihttps://doi.org/10.1016/j.solener.2011.07.009
dc.identifier.urihttps://hdl.handle.net/20.500.12491/6865
dc.identifier.volume85en_US
dc.identifier.wosWOS:000295567500009en_US
dc.identifier.wosqualityQ2en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.institutionauthorÇelik, Ali Naci
dc.language.isoenen_US
dc.publisherPergamon-Elsevier Science Ltden_US
dc.relation.ispartofSolar Energyen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectArtificial Neural Network Modellingen_US
dc.subjectModelling Photovoltaic Cellsen_US
dc.subjectAnalytical Modellingen_US
dc.subjectGeneralised Regression Neural Networken_US
dc.titleArtificial neural network modelling and experimental verification of the operating current of mono-crystalline photovoltaic modulesen_US
dc.typeArticleen_US

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