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Harmonic identification using parallel neural networks in single-phase systems

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dc.contributor.authordo Nascimento, Claudionor Francisco
dc.contributor.authorde Oliveira, Azauri Albano
dc.contributor.authorGoedtel, Alessandro
dc.contributor.authorAmaral Serni, Paulo Jose [UNESP]
dc.contributor.institutionFed Univ Technol UTFPR
dc.contributor.institutionUniversidade Federal do ABC (UFABC)
dc.contributor.institutionUniversidade de São Paulo (USP)
dc.contributor.institutionUniversidade Estadual Paulista (Unesp)
dc.date.accessioned2014-05-20T15:33:18Z
dc.date.available2014-05-20T15:33:18Z
dc.date.issued2011-03-01
dc.description.abstractIn this paper, artificial neural networks are employed in a novel approach to identify harmonic components of single-phase nonlinear load currents, whose amplitude and phase angle are subject to unpredictable changes, even in steady-state. The first six harmonic current components are identified through the variation analysis of waveform characteristics. The effectiveness of this method is tested by applying it to the model of a single-phase active power filter, dedicated to the selective compensation of harmonic current drained by an AC controller. Simulation and experimental results are presented to validate the proposed approach. (C) 2010 Elsevier B. V. All rights reserved.en
dc.description.affiliationFed Univ Technol UTFPR, Dept Elect Engn, BR-86300000 Cornelio Procopio, PR, Brazil
dc.description.affiliationFed Univ ABC UFABC, CECS, BR-09210170 Santo Andre, SP, Brazil
dc.description.affiliationUniv São Paulo USP, Dept Elect Engn, BR-13566590 São Carlos, SP, Brazil
dc.description.affiliationSão Paulo State Univ UNESP, FEB, BR-17033360 Bauru, SP, Brazil
dc.description.affiliationUnespSão Paulo State Univ UNESP, FEB, BR-17033360 Bauru, SP, Brazil
dc.description.sponsorshipConselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
dc.description.sponsorshipFundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
dc.description.sponsorshipIdCNPq: 142128/2005-8
dc.description.sponsorshipIdCNPq: 474290/2008-5
dc.description.sponsorshipIdFAPESP: 06/56093-3
dc.format.extent2178-2185
dc.identifierhttp://dx.doi.org/10.1016/j.asoc.2010.07.017
dc.identifier.citationApplied Soft Computing. Amsterdam: Elsevier B.V., v. 11, n. 2, p. 2178-2185, 2011.
dc.identifier.doi10.1016/j.asoc.2010.07.017
dc.identifier.issn1568-4946
dc.identifier.urihttp://hdl.handle.net/11449/41969
dc.identifier.wosWOS:000286373200070
dc.language.isoeng
dc.publisherElsevier B.V.
dc.relation.ispartofApplied Soft Computing
dc.relation.ispartofjcr3.907
dc.relation.ispartofsjr1,199
dc.rights.accessRightsAcesso restrito
dc.sourceWeb of Science
dc.subjectHarmonic distortionen
dc.subjectNeural network applicationen
dc.subjectSingle-phase power systemen
dc.subjectPower electronicsen
dc.titleHarmonic identification using parallel neural networks in single-phase systemsen
dc.typeArtigo
dcterms.licensehttp://www.elsevier.com/about/open-access/open-access-policies/article-posting-policy
dcterms.rightsHolderElsevier B.V.

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