Wavelet-artificial immune system algorithm applied to voltage disturbance diagnosis in electrical distribution systems
Autor(a) principal: | |
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Data de Publicação: | 2015 |
Outros Autores: | , |
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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Repositório Institucional da UNESP |
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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/openAccess2024-07-04T19:05:42Zoai:repositorio.unesp.br:11449/171977Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T13:46:38.294279Repositório 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_ |
1808128275272171520 |