Fuzzy wavelet network identification of optimum operating point of non-crystalline silicon solar cells

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dc.contributor.authorSyafaruddin
dc.contributor.authorKaratepe, Engin
dc.contributor.authorHiyama, Takashi
dc.date.accessioned2019-10-27T21:34:39Z
dc.date.available2019-10-27T21:34:39Z
dc.date.issued2012
dc.departmentEge Üniversitesien_US
dc.description.abstractThe emerging non-crystalline silicon (c-Si) solar cell technologies are starting to make significant inroads into solar cell markets. Most of the researchers have focused on c-Si solar cell in maximum power points tracking applications of photovoltaic (PV) systems. However, the characteristics of non-c-Si solar cell technologies at maximum power point (MPP) have different trends in current-voltage characteristics. For this reason, determining the optimum operating point is very important for different solar cell technologies to increase the efficiency of PV systems. In this paper, it has been shown that the use of fuzzy system coupled with a discrete wavelet network in Takagi-Sugeno type model structure is capable of identifying the MPP voltage of different non-c-Si solar cells with very high accuracy. The performance of the fuzzy-wavelet network (FWN) method has been compared with other ANN structures, such as radial basis function (RBF), adaptive neuro-fuzzy inference system (ANFIS) and three layered feed-forward neural network (TFFN). The simulation results show that the single FWN architecture has superior approximation accuracy over the other methods and a very good generalization capability for different operating conditions and different technologies. (C) 2011 Elsevier Ltd. All rights reserved.en_US
dc.identifier.doi10.1016/j.camwa.2011.10.073
dc.identifier.endpage82en_US
dc.identifier.issn0898-1221
dc.identifier.issn0898-1221en_US
dc.identifier.issue1en_US
dc.identifier.scopusqualityN/Aen_US
dc.identifier.startpage68en_US
dc.identifier.urihttps://doi.org/10.1016/j.camwa.2011.10.073
dc.identifier.urihttps://hdl.handle.net/11454/45650
dc.identifier.volume63en_US
dc.identifier.wosWOS:000299757600008en_US
dc.identifier.wosqualityQ1en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherPergamon-Elsevier Science Ltden_US
dc.relation.ispartofComputers & Mathematics With Applicationsen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectFuzzy-wavelet networken_US
dc.subjectSolar cellen_US
dc.subjectPhotovoltaicen_US
dc.subjectSystem identificationen_US
dc.subjectMaximum power pointen_US
dc.titleFuzzy wavelet network identification of optimum operating point of non-crystalline silicon solar cellsen_US
dc.typeArticleen_US

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