Investigation of ANN performance for tracking the optimum points of PV module under partially shaded conditions

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dc.contributor.authorSyafaruddin
dc.contributor.authorHiyama T.
dc.contributor.authorKaratepe E.
dc.date.accessioned2019-10-26T22:20:32Z
dc.date.available2019-10-26T22:20:32Z
dc.date.issued2010
dc.departmentEge Üniversitesien_US
dc.description2010 9th International Power and Energy Conference, IPEC 2010 -- 27 October 2010 through 29 October 2010 -- Singapore -- 83829en_US
dc.description.abstractSolving partially shaded condition still remains an important task in the PV system practice. Under such condition, the global maximum point shifts continuously in wide voltage range from the local maxima, which make it difficult for conventional controllers. Intelligent techniques based on artificial neural network are well-known as the promising methods to identify the global maxima. However, there are many variants of neural networks and they have strong and weak points during the implementation. This paper investigates the performance of radial basis function (RBF) neural network and three layered feed-forward neural network (TFFN) under partial shadow operation of PV module. These two ANN structures are well-recognized for optimization, forecasting and control in PV system application due to the simplicity of structure and high performance accuracy. The investigation is focused on the network structure, training and validation process of these methods. To determine to which method is preferable to handle this task, the adaptive neuro-fuzzy inference system (ANFIS) is used as the comparator. The proposed method is verified and tested using developed real-time simulator. ©2010 IEEE.en_US
dc.identifier.doi10.1109/IPECON.2010.5697002
dc.identifier.endpage1191en_US
dc.identifier.isbn9781424473991
dc.identifier.scopusqualityN/Aen_US
dc.identifier.startpage1186en_US
dc.identifier.urihttps://doi.org/10.1109/IPECON.2010.5697002
dc.identifier.urihttps://hdl.handle.net/11454/19589
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.relation.ispartof2010 9th International Power and Energy Conference, IPEC 2010en_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectANFISen_US
dc.subjectOptimum pointsen_US
dc.subjectPartially shaded conditionsen_US
dc.subjectRBFen_US
dc.subjectTFFNen_US
dc.titleInvestigation of ANN performance for tracking the optimum points of PV module under partially shaded conditionsen_US
dc.typeConference Objecten_US

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