Wavelet-artificial immune system algorithm applied to voltage disturbance diagnosis in electrical distribution systems

Detalhes bibliográficos
Autor(a) principal: Lima, Fernando P.A. [UNESP]
Data de Publicação: 2015
Outros Autores: Lotufo, Anna Diva P. [UNESP], Minussi, Carlos Roberto [UNESP]
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Institucional da UNESP
Texto Completo: http://dx.doi.org/10.1049/iet-gtd.2014.1102
http://hdl.handle.net/11449/171977
Resumo: This study presents a new approach to detecting and classifying voltage disturbances in electrical distribution systems based on wavelet transform and artificial immune algorithm. This proposal unifies the negative selection artificial immune algorithm with the discrete wavelet transform concept. Thus, the measurements obtained in a distribution substation by the supervisory control and data acquisition acquisition system are transformed into the wavelet domain. Afterward, a negative selection artificial immune system realises the diagnosis, identifying and classifying the abnormalities. The principal application of this tool is to aid the system operation during faults as well as to supervise the protection system. To evaluate the performance of the proposed method, two distribution systems were modelled in EMTP software: an 84-bus test system and a 134-bus real system. The results show a good performance, emphasising the precision of the diagnosis.
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spelling Wavelet-artificial immune system algorithm applied to voltage disturbance diagnosis in electrical distribution systemsThis study presents a new approach to detecting and classifying voltage disturbances in electrical distribution systems based on wavelet transform and artificial immune algorithm. This proposal unifies the negative selection artificial immune algorithm with the discrete wavelet transform concept. Thus, the measurements obtained in a distribution substation by the supervisory control and data acquisition acquisition system are transformed into the wavelet domain. Afterward, a negative selection artificial immune system realises the diagnosis, identifying and classifying the abnormalities. The principal application of this tool is to aid the system operation during faults as well as to supervise the protection system. To evaluate the performance of the proposed method, two distribution systems were modelled in EMTP software: an 84-bus test system and a 134-bus real system. The results show a good performance, emphasising the precision of the diagnosis.Electrical Engineering Department, Faculty of Engineering of Ilha Solteira, UNESP, Universidade Estadual Paulista 'Júlio de Mesquita Filho', Av. Brasil 56, P.O. Box 31Electrical Engineering Department, Faculty of Engineering of Ilha Solteira, UNESP, Universidade Estadual Paulista 'Júlio de Mesquita Filho', Av. Brasil 56, P.O. Box 31Universidade Estadual Paulista (Unesp)Lima, Fernando P.A. [UNESP]Lotufo, Anna Diva P. [UNESP]Minussi, Carlos Roberto [UNESP]2018-12-11T16:57:59Z2018-12-11T16:57:59Z2015-01-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article1104-1111application/pdfhttp://dx.doi.org/10.1049/iet-gtd.2014.1102IET Generation, Transmission and Distribution, v. 9, n. 11, p. 1104-1111, 2015.1751-8687http://hdl.handle.net/11449/17197710.1049/iet-gtd.2014.11022-s2.0-849385672852-s2.0-84938567285.pdfScopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengIET Generation, Transmission and Distribution0,907info:eu-repo/semantics/openAccess2023-10-02T06:05:41Zoai:repositorio.unesp.br:11449/171977Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462023-10-02T06:05:41Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false
dc.title.none.fl_str_mv Wavelet-artificial immune system algorithm applied to voltage disturbance diagnosis in electrical distribution systems
title Wavelet-artificial immune system algorithm applied to voltage disturbance diagnosis in electrical distribution systems
spellingShingle Wavelet-artificial immune system algorithm applied to voltage disturbance diagnosis in electrical distribution systems
Lima, Fernando P.A. [UNESP]
title_short Wavelet-artificial immune system algorithm applied to voltage disturbance diagnosis in electrical distribution systems
title_full Wavelet-artificial immune system algorithm applied to voltage disturbance diagnosis in electrical distribution systems
title_fullStr Wavelet-artificial immune system algorithm applied to voltage disturbance diagnosis in electrical distribution systems
title_full_unstemmed Wavelet-artificial immune system algorithm applied to voltage disturbance diagnosis in electrical distribution systems
title_sort Wavelet-artificial immune system algorithm applied to voltage disturbance diagnosis in electrical distribution systems
author Lima, Fernando P.A. [UNESP]
author_facet Lima, Fernando P.A. [UNESP]
Lotufo, Anna Diva P. [UNESP]
Minussi, Carlos Roberto [UNESP]
author_role author
author2 Lotufo, Anna Diva P. [UNESP]
Minussi, Carlos Roberto [UNESP]
author2_role author
author
dc.contributor.none.fl_str_mv Universidade Estadual Paulista (Unesp)
dc.contributor.author.fl_str_mv Lima, Fernando P.A. [UNESP]
Lotufo, Anna Diva P. [UNESP]
Minussi, Carlos Roberto [UNESP]
description This study presents a new approach to detecting and classifying voltage disturbances in electrical distribution systems based on wavelet transform and artificial immune algorithm. This proposal unifies the negative selection artificial immune algorithm with the discrete wavelet transform concept. Thus, the measurements obtained in a distribution substation by the supervisory control and data acquisition acquisition system are transformed into the wavelet domain. Afterward, a negative selection artificial immune system realises the diagnosis, identifying and classifying the abnormalities. The principal application of this tool is to aid the system operation during faults as well as to supervise the protection system. To evaluate the performance of the proposed method, two distribution systems were modelled in EMTP software: an 84-bus test system and a 134-bus real system. The results show a good performance, emphasising the precision of the diagnosis.
publishDate 2015
dc.date.none.fl_str_mv 2015-01-01
2018-12-11T16:57:59Z
2018-12-11T16:57:59Z
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.uri.fl_str_mv http://dx.doi.org/10.1049/iet-gtd.2014.1102
IET Generation, Transmission and Distribution, v. 9, n. 11, p. 1104-1111, 2015.
1751-8687
http://hdl.handle.net/11449/171977
10.1049/iet-gtd.2014.1102
2-s2.0-84938567285
2-s2.0-84938567285.pdf
url http://dx.doi.org/10.1049/iet-gtd.2014.1102
http://hdl.handle.net/11449/171977
identifier_str_mv IET Generation, Transmission and Distribution, v. 9, n. 11, p. 1104-1111, 2015.
1751-8687
10.1049/iet-gtd.2014.1102
2-s2.0-84938567285
2-s2.0-84938567285.pdf
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv IET Generation, Transmission and Distribution
0,907
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv 1104-1111
application/pdf
dc.source.none.fl_str_mv Scopus
reponame:Repositório Institucional da UNESP
instname:Universidade Estadual Paulista (UNESP)
instacron:UNESP
instname_str Universidade Estadual Paulista (UNESP)
instacron_str UNESP
institution UNESP
reponame_str Repositório Institucional da UNESP
collection Repositório Institucional da UNESP
repository.name.fl_str_mv Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)
repository.mail.fl_str_mv
_version_ 1799964403938885632

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