Wavelet-fuzzy power quality diagnosis system with inference method based on overlap functions: case study in an AC microgrid
Autor(a) principal: | |
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Data de Publicação: | 2019 |
Outros Autores: | , , , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UFRN |
Texto Completo: | https://repositorio.ufrn.br/jspui/handle/123456789/29808 |
Resumo: | This work proposes a wavelet-fuzzy power quality (PQ) diagnosis method able to evaluate the PQ impact of steady-state (stationary) PQ events in alternating current (AC) microgrids considering the influence of the power level penetration. The proposed method is composed by a wavelet packet-based signal processing to compute the root mean square (RMS) and steady-state PQ indices of measured voltages and currents, providing accurate results even if transient disturbances take place. Thereafter, a cascade-type hierarchical fuzzy system receives the PQ indices and performs the power quality diagnosis to evaluate the impacts of disturbances on electrical system power quality. The proposed method considers subjectivities of several PQ standards simultaneously and applies an adaptive algorithm that allows the evaluation of the PQ diagnosis from the total harmonic distortion of currents considering different levels of power penetration of microgrids. Experimental results obtained from an ac microgrid laboratory setup evaluates the proposed PQ diagnosis method. In addition, the fuzzy system uses a new inference concept based on an extended n-dimensional overlap function |
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Nolasco, Diego H. S.Costa, Flávio BezerraPalmeira, Eduardo SilvaAlves, Denis KeutonBedregal, Benjamín Rene CallejasRocha, Thiago de Oliveira AlvesRibeiro, Ricardo Lúcio de AraújoSilva, Juliano Costa Leal da2020-08-13T00:27:49Z2020-08-13T00:27:49Z2019-05-30NOLASCO, D.H.S.; COSTA, F.B.; PALMEIRA, E.S.; ALVES, D.K.; BEDREGAL, B.R.C.; ROCHA, T.O.A.; RIBEIRO, R.L.A.; SILVA, J.C.L.. Wavelet-fuzzy power quality diagnosis system with inference method based on overlap functions: case study in an ac microgrid. Engineering Applications of Artificial Intelligence, [s.l.], v. 85, p. 284-294, out. 2019. Disponível em: https://www.sciencedirect.com/science/article/abs/pii/S0952197619301241?via%3Dihub#!. Acesso em: 10 ago. 2020. http://dx.doi.org/10.1016/j.engappai.2019.05.0160952-1976https://repositorio.ufrn.br/jspui/handle/123456789/2980810.1016/j.engappai.2019.05.016ElsevierPower qualityMicrogridWavelet packetHierarchical fuzzy systemExtended overlap functionWavelet-fuzzy power quality diagnosis system with inference method based on overlap functions: case study in an AC microgridinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleThis work proposes a wavelet-fuzzy power quality (PQ) diagnosis method able to evaluate the PQ impact of steady-state (stationary) PQ events in alternating current (AC) microgrids considering the influence of the power level penetration. The proposed method is composed by a wavelet packet-based signal processing to compute the root mean square (RMS) and steady-state PQ indices of measured voltages and currents, providing accurate results even if transient disturbances take place. Thereafter, a cascade-type hierarchical fuzzy system receives the PQ indices and performs the power quality diagnosis to evaluate the impacts of disturbances on electrical system power quality. The proposed method considers subjectivities of several PQ standards simultaneously and applies an adaptive algorithm that allows the evaluation of the PQ diagnosis from the total harmonic distortion of currents considering different levels of power penetration of microgrids. Experimental results obtained from an ac microgrid laboratory setup evaluates the proposed PQ diagnosis method. In addition, the fuzzy system uses a new inference concept based on an extended n-dimensional overlap functionengreponame:Repositório Institucional da UFRNinstname:Universidade Federal do Rio Grande do Norte (UFRN)instacron:UFRNinfo:eu-repo/semantics/openAccessCC-LICENSElicense_rdflicense_rdfapplication/rdf+xml; charset=utf-8914https://repositorio.ufrn.br/bitstream/123456789/29808/2/license_rdf4d2950bda3d176f570a9f8b328dfbbefMD52LICENSElicense.txtlicense.txttext/plain; charset=utf-81484https://repositorio.ufrn.br/bitstream/123456789/29808/3/license.txte9597aa2854d128fd968be5edc8a28d9MD53TEXTWavelet-fuzzyPowerQuality_COSTA_2019.pdf.txtWavelet-fuzzyPowerQuality_COSTA_2019.pdf.txtExtracted texttext/plain64696https://repositorio.ufrn.br/bitstream/123456789/29808/4/Wavelet-fuzzyPowerQuality_COSTA_2019.pdf.txt5baca12ac04b92f40e35ddbe3a9d5c9cMD54THUMBNAILWavelet-fuzzyPowerQuality_COSTA_2019.pdf.jpgWavelet-fuzzyPowerQuality_COSTA_2019.pdf.jpgGenerated Thumbnailimage/jpeg1735https://repositorio.ufrn.br/bitstream/123456789/29808/5/Wavelet-fuzzyPowerQuality_COSTA_2019.pdf.jpg3f5d7365657bbd95276c47ee9dec2e27MD55123456789/298082023-02-03 16:14:08.409oai:https://repositorio.ufrn.br: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Repositório de PublicaçõesPUBhttp://repositorio.ufrn.br/oai/opendoar:2023-02-03T19:14:08Repositório Institucional da UFRN - Universidade Federal do Rio Grande do Norte (UFRN)false |
dc.title.pt_BR.fl_str_mv |
Wavelet-fuzzy power quality diagnosis system with inference method based on overlap functions: case study in an AC microgrid |
title |
Wavelet-fuzzy power quality diagnosis system with inference method based on overlap functions: case study in an AC microgrid |
spellingShingle |
Wavelet-fuzzy power quality diagnosis system with inference method based on overlap functions: case study in an AC microgrid Nolasco, Diego H. S. Power quality Microgrid Wavelet packet Hierarchical fuzzy system Extended overlap function |
title_short |
Wavelet-fuzzy power quality diagnosis system with inference method based on overlap functions: case study in an AC microgrid |
title_full |
Wavelet-fuzzy power quality diagnosis system with inference method based on overlap functions: case study in an AC microgrid |
title_fullStr |
Wavelet-fuzzy power quality diagnosis system with inference method based on overlap functions: case study in an AC microgrid |
title_full_unstemmed |
Wavelet-fuzzy power quality diagnosis system with inference method based on overlap functions: case study in an AC microgrid |
title_sort |
Wavelet-fuzzy power quality diagnosis system with inference method based on overlap functions: case study in an AC microgrid |
author |
Nolasco, Diego H. S. |
author_facet |
Nolasco, Diego H. S. Costa, Flávio Bezerra Palmeira, Eduardo Silva Alves, Denis Keuton Bedregal, Benjamín Rene Callejas Rocha, Thiago de Oliveira Alves Ribeiro, Ricardo Lúcio de Araújo Silva, Juliano Costa Leal da |
author_role |
author |
author2 |
Costa, Flávio Bezerra Palmeira, Eduardo Silva Alves, Denis Keuton Bedregal, Benjamín Rene Callejas Rocha, Thiago de Oliveira Alves Ribeiro, Ricardo Lúcio de Araújo Silva, Juliano Costa Leal da |
author2_role |
author author author author author author author |
dc.contributor.author.fl_str_mv |
Nolasco, Diego H. S. Costa, Flávio Bezerra Palmeira, Eduardo Silva Alves, Denis Keuton Bedregal, Benjamín Rene Callejas Rocha, Thiago de Oliveira Alves Ribeiro, Ricardo Lúcio de Araújo Silva, Juliano Costa Leal da |
dc.subject.por.fl_str_mv |
Power quality Microgrid Wavelet packet Hierarchical fuzzy system Extended overlap function |
topic |
Power quality Microgrid Wavelet packet Hierarchical fuzzy system Extended overlap function |
description |
This work proposes a wavelet-fuzzy power quality (PQ) diagnosis method able to evaluate the PQ impact of steady-state (stationary) PQ events in alternating current (AC) microgrids considering the influence of the power level penetration. The proposed method is composed by a wavelet packet-based signal processing to compute the root mean square (RMS) and steady-state PQ indices of measured voltages and currents, providing accurate results even if transient disturbances take place. Thereafter, a cascade-type hierarchical fuzzy system receives the PQ indices and performs the power quality diagnosis to evaluate the impacts of disturbances on electrical system power quality. The proposed method considers subjectivities of several PQ standards simultaneously and applies an adaptive algorithm that allows the evaluation of the PQ diagnosis from the total harmonic distortion of currents considering different levels of power penetration of microgrids. Experimental results obtained from an ac microgrid laboratory setup evaluates the proposed PQ diagnosis method. In addition, the fuzzy system uses a new inference concept based on an extended n-dimensional overlap function |
publishDate |
2019 |
dc.date.issued.fl_str_mv |
2019-05-30 |
dc.date.accessioned.fl_str_mv |
2020-08-13T00:27:49Z |
dc.date.available.fl_str_mv |
2020-08-13T00:27:49Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.citation.fl_str_mv |
NOLASCO, D.H.S.; COSTA, F.B.; PALMEIRA, E.S.; ALVES, D.K.; BEDREGAL, B.R.C.; ROCHA, T.O.A.; RIBEIRO, R.L.A.; SILVA, J.C.L.. Wavelet-fuzzy power quality diagnosis system with inference method based on overlap functions: case study in an ac microgrid. Engineering Applications of Artificial Intelligence, [s.l.], v. 85, p. 284-294, out. 2019. Disponível em: https://www.sciencedirect.com/science/article/abs/pii/S0952197619301241?via%3Dihub#!. Acesso em: 10 ago. 2020. http://dx.doi.org/10.1016/j.engappai.2019.05.016 |
dc.identifier.uri.fl_str_mv |
https://repositorio.ufrn.br/jspui/handle/123456789/29808 |
dc.identifier.issn.none.fl_str_mv |
0952-1976 |
dc.identifier.doi.none.fl_str_mv |
10.1016/j.engappai.2019.05.016 |
identifier_str_mv |
NOLASCO, D.H.S.; COSTA, F.B.; PALMEIRA, E.S.; ALVES, D.K.; BEDREGAL, B.R.C.; ROCHA, T.O.A.; RIBEIRO, R.L.A.; SILVA, J.C.L.. Wavelet-fuzzy power quality diagnosis system with inference method based on overlap functions: case study in an ac microgrid. Engineering Applications of Artificial Intelligence, [s.l.], v. 85, p. 284-294, out. 2019. Disponível em: https://www.sciencedirect.com/science/article/abs/pii/S0952197619301241?via%3Dihub#!. Acesso em: 10 ago. 2020. http://dx.doi.org/10.1016/j.engappai.2019.05.016 0952-1976 10.1016/j.engappai.2019.05.016 |
url |
https://repositorio.ufrn.br/jspui/handle/123456789/29808 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
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openAccess |
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Elsevier |
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Elsevier |
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UFRN |
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UFRN |
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