Analysis of high-voltage substations design using artificial neural networks

Detalhes bibliográficos
Autor(a) principal: Nunes da Silva, Ivan [UNESP]
Data de Publicação: 1999
Outros Autores: Nunes de Souza, Andre [UNESP]
Tipo de documento: Artigo de conferência
Idioma: eng
Título da fonte: Repositório Institucional da UNESP
Texto Completo: http://hdl.handle.net/11449/219224
Resumo: This paper demonstrates that artificial neural networks can be used effectively for the identification and estimation of parameters related to analysis and design of high-voltage substations. More specifically, the neural networks are used to compute electrical field intensity and critical disruptive voltage in substations taking into account several atmospheric and structural factors, such as pressure, temperature, humidity, distance between phases, height of bus bars, and wave forms. Examples of simulation of tests are presented to validate the proposed approach. The results that were obtained by experimental evidences and numerical simulations allowed the proposition of new rules about the specification of substations.
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spelling Analysis of high-voltage substations design using artificial neural networksThis paper demonstrates that artificial neural networks can be used effectively for the identification and estimation of parameters related to analysis and design of high-voltage substations. More specifically, the neural networks are used to compute electrical field intensity and critical disruptive voltage in substations taking into account several atmospheric and structural factors, such as pressure, temperature, humidity, distance between phases, height of bus bars, and wave forms. Examples of simulation of tests are presented to validate the proposed approach. The results that were obtained by experimental evidences and numerical simulations allowed the proposition of new rules about the specification of substations.State Univ of Sao Paulo - UNESP, BauruState Univ of Sao Paulo - UNESP, BauruUniversidade Estadual Paulista (UNESP)Nunes da Silva, Ivan [UNESP]Nunes de Souza, Andre [UNESP]2022-04-28T18:54:27Z2022-04-28T18:54:27Z1999-12-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/conferenceObjectIEE Conference Publication, v. 1, n. 467, 1999.0537-9989http://hdl.handle.net/11449/2192242-s2.0-0033340167Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengIEE Conference Publicationinfo:eu-repo/semantics/openAccess2022-04-28T18:54:27Zoai:repositorio.unesp.br:11449/219224Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-05-23T11:46:10.495285Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false
dc.title.none.fl_str_mv Analysis of high-voltage substations design using artificial neural networks
title Analysis of high-voltage substations design using artificial neural networks
spellingShingle Analysis of high-voltage substations design using artificial neural networks
Nunes da Silva, Ivan [UNESP]
title_short Analysis of high-voltage substations design using artificial neural networks
title_full Analysis of high-voltage substations design using artificial neural networks
title_fullStr Analysis of high-voltage substations design using artificial neural networks
title_full_unstemmed Analysis of high-voltage substations design using artificial neural networks
title_sort Analysis of high-voltage substations design using artificial neural networks
author Nunes da Silva, Ivan [UNESP]
author_facet Nunes da Silva, Ivan [UNESP]
Nunes de Souza, Andre [UNESP]
author_role author
author2 Nunes de Souza, Andre [UNESP]
author2_role author
dc.contributor.none.fl_str_mv Universidade Estadual Paulista (UNESP)
dc.contributor.author.fl_str_mv Nunes da Silva, Ivan [UNESP]
Nunes de Souza, Andre [UNESP]
description This paper demonstrates that artificial neural networks can be used effectively for the identification and estimation of parameters related to analysis and design of high-voltage substations. More specifically, the neural networks are used to compute electrical field intensity and critical disruptive voltage in substations taking into account several atmospheric and structural factors, such as pressure, temperature, humidity, distance between phases, height of bus bars, and wave forms. Examples of simulation of tests are presented to validate the proposed approach. The results that were obtained by experimental evidences and numerical simulations allowed the proposition of new rules about the specification of substations.
publishDate 1999
dc.date.none.fl_str_mv 1999-12-01
2022-04-28T18:54:27Z
2022-04-28T18:54:27Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/conferenceObject
format conferenceObject
status_str publishedVersion
dc.identifier.uri.fl_str_mv IEE Conference Publication, v. 1, n. 467, 1999.
0537-9989
http://hdl.handle.net/11449/219224
2-s2.0-0033340167
identifier_str_mv IEE Conference Publication, v. 1, n. 467, 1999.
0537-9989
2-s2.0-0033340167
url http://hdl.handle.net/11449/219224
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv IEE Conference Publication
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
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_ 1803045878587457536

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