Detection and classification of voltage disturbances using a Fuzzy-ARTMAP-wavelet network

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dc.contributor.authorDecanini, Jose G. M. S. [UNESP]
dc.contributor.authorTonelli-Neto, Mauro S. [UNESP]
dc.contributor.authorMalange, Fernando C. V. [UNESP]
dc.contributor.authorMinussi, Carlos R. [UNESP]
dc.contributor.institutionUniversidade Estadual Paulista (Unesp)
dc.date.accessioned2014-05-20T13:29:07Z
dc.date.available2014-05-20T13:29:07Z
dc.date.issued2011-12-01
dc.description.abstractThis paper presents a method for automatic detection and classification of voltage disturbances for problems related to power quality using signal processing techniques and intelligent systems. This support tool for decision making is composed of four modules. The first module continuously evaluates the system's operation state. The second module extracts the essential features from the three-phase voltage signal based on the discrete wavelet transform, multi resolution analysis and entropy norm concepts. The signal signature is processed via standardization and codification in the third module. The fourth module classifies the type of disorder using a Fuzzy-ARTMAP neural network. A total of 7023 power quality events, including voltage swell, voltage sag, outage, harmonics, swell with harmonics, sag with harmonics, oscillatory transient and flicker, were obtained through mathematical models and simulations using the ATP software. To demonstrate the performance of this method, an application is submitted considering a real electric energy distribution system composed of 134 buses with measurements performed on a 13.8 kV and 7.065 MVA feeder. The results indicate that the proposed method is efficient, robust and has high computing performance (low processing time), which allows, a priori, its application in real time. (C) 2011 Elsevier B.V. All rights reserved.en
dc.description.affiliationUniv Estadual Paulista, UNESP, Dept Elect Engn, BR-15385000 Ilha Solteira, SP, Brazil
dc.description.affiliationUnespUniv Estadual Paulista, UNESP, Dept Elect Engn, BR-15385000 Ilha Solteira, SP, Brazil
dc.description.sponsorshipFundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
dc.description.sponsorshipConselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
dc.format.extent2057-2065
dc.identifierhttp://dx.doi.org/10.1016/j.epsr.2011.07.018
dc.identifier.citationElectric Power Systems Research. Lausanne: Elsevier B.V. Sa, v. 81, n. 12, p. 2057-2065, 2011.
dc.identifier.doi10.1016/j.epsr.2011.07.018
dc.identifier.issn0378-7796
dc.identifier.urihttp://hdl.handle.net/11449/9781
dc.identifier.wosWOS:000296042300001
dc.language.isoeng
dc.publisherElsevier B.V. Sa
dc.relation.ispartofElectric Power Systems Research
dc.relation.ispartofjcr2.856
dc.relation.ispartofsjr1,048
dc.rights.accessRightsAcesso restrito
dc.sourceWeb of Science
dc.subjectPower qualityen
dc.subjectWavelet transformen
dc.subjectDisturbance diagnosisen
dc.subjectFuzzy-ARTMAP neural networken
dc.subjectElectric power systemsen
dc.titleDetection and classification of voltage disturbances using a Fuzzy-ARTMAP-wavelet networken
dc.typeArtigo
dcterms.licensehttp://www.elsevier.com/about/open-access/open-access-policies/article-posting-policy
dcterms.rightsHolderElsevier B.V. Sa
unesp.author.lattes7166279400544764[4]
unesp.author.orcid0000-0001-6428-4506[4]
unesp.campusUniversidade Estadual Paulista (Unesp), Faculdade de Engenharia, Ilha Solteirapt

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