ANN based real-time estimation of power generation of different PV module types

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dc.contributor.authorSyafaruddin
dc.contributor.authorKaratepe E.
dc.contributor.authorHiyama T.
dc.date.accessioned2019-10-26T22:57:59Z
dc.date.available2019-10-26T22:57:59Z
dc.date.issued2009
dc.departmentEge Üniversitesien_US
dc.description.abstractDistributed generation is expected to become more important in the future generation system. Utilities need to find solutions that help manage resources more efficiently. Effective smart grid solutions have been experienced by using real-time data to help refine and pinpoint inefficiencies for maintaining secure and reliable operating conditions. This paper proposes the application of Artificial Neural Network (ANN) for the real-time estimation of the maximum power generation of PV modules of different technologies. An intelligent technique is necessary required in this case due to the relationship between the maximum power of PV modules and the open circuit voltage and temperature is nonlinear and can't be easily expressed by an analytical expression for each technology. The proposed ANN method is using input signals of open circuit voltage and cell temperature instead of irradiance and ambient temperature to determine the estimated maximum power generation of PV modules. It is important for the utility to have the capability to perform this estimation for optimal operating points and diagnostic purposes that may be an early indicator of a need for maintenance and optimal energy management. The proposed method is accurately verified through a developed real-time simulator on the daily basis of irradiance and cell temperature changes. © 2009 The Institute of Electrical Engineers of Japan.en_US
dc.identifier.endpage790en_US
dc.identifier.issn0385-4213
dc.identifier.issn0385-4213en_US
dc.identifier.issue6en_US
dc.identifier.scopusqualityQ3en_US
dc.identifier.startpage6+783en_US
dc.identifier.urihttps://hdl.handle.net/11454/20488
dc.identifier.volume129en_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.relation.ispartofIEEJ Transactions on Power and Energyen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectCadmium tellurideen_US
dc.subjectCrystalline siliconen_US
dc.subjectPhotovoltaicen_US
dc.subjectPower estimationen_US
dc.subjectReal-time simulatoren_US
dc.subjectTriple junction amorphous siliconen_US
dc.titleANN based real-time estimation of power generation of different PV module typesen_US
dc.typeArticleen_US

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