Fault section estimation in electric power systems using an artificial immune system algorithm
Autor(a) principal: | |
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Data de Publicação: | 2008 |
Outros Autores: | , |
Tipo de documento: | Artigo de conferência |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UNESP |
Texto Completo: | http://hdl.handle.net/11449/228053 |
Resumo: | This work proposes an unconstrained binary programming (UBP) model for fault section estimation in power systems. UBP model consists in a set of equations that represent in a logical way the expected states of the relays of the apparatus protection system. An artificial immune system algorithm (AISA) is developed in order to find the correct fault section estimate provided by the data from the supervisory control and data acquisition (SCADA) system. The proposed methodology is tested using part of the South-Brazilian electric power system. Control parameters of the AISA are calibrated to increase the efficiency and velocity of the algorithm. Results show the potential and the efficiency of the proposed methodology to fault section estimation online in electric power systems. |
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Repositório Institucional da UNESP |
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spelling |
Fault section estimation in electric power systems using an artificial immune system algorithmArtificial immune systemsFault section estimationPower system protectionThis work proposes an unconstrained binary programming (UBP) model for fault section estimation in power systems. UBP model consists in a set of equations that represent in a logical way the expected states of the relays of the apparatus protection system. An artificial immune system algorithm (AISA) is developed in order to find the correct fault section estimate provided by the data from the supervisory control and data acquisition (SCADA) system. The proposed methodology is tested using part of the South-Brazilian electric power system. Control parameters of the AISA are calibrated to increase the efficiency and velocity of the algorithm. Results show the potential and the efficiency of the proposed methodology to fault section estimation online in electric power systems.Reserch Group in Electric Power System Planning, Department of Electrical Engineering, Engineering College of Ilha Solteira, São Paulo State University, UNESP, Post Office Box 31Reserch Group in Electric Power System Planning, Department of Electrical Engineering, Engineering College of Ilha Solteira, São Paulo State University, UNESP, Post Office Box 31Universidade Estadual Paulista (UNESP)Leão, Fábio Bertequini [UNESP]Pereira, Rodrigo A. F. [UNESP]Mantovani, José R. S. [UNESP]2022-04-29T07:26:29Z2022-04-29T07:26:29Z2008-01-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/conferenceObject16th Power Systems Computation Conference, PSCC 2008.http://hdl.handle.net/11449/2280532-s2.0-84944097046Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPeng16th Power Systems Computation Conference, PSCC 2008info:eu-repo/semantics/openAccess2022-04-29T07:26:29Zoai:repositorio.unesp.br:11449/228053Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462022-04-29T07:26:29Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false |
dc.title.none.fl_str_mv |
Fault section estimation in electric power systems using an artificial immune system algorithm |
title |
Fault section estimation in electric power systems using an artificial immune system algorithm |
spellingShingle |
Fault section estimation in electric power systems using an artificial immune system algorithm Leão, Fábio Bertequini [UNESP] Artificial immune systems Fault section estimation Power system protection |
title_short |
Fault section estimation in electric power systems using an artificial immune system algorithm |
title_full |
Fault section estimation in electric power systems using an artificial immune system algorithm |
title_fullStr |
Fault section estimation in electric power systems using an artificial immune system algorithm |
title_full_unstemmed |
Fault section estimation in electric power systems using an artificial immune system algorithm |
title_sort |
Fault section estimation in electric power systems using an artificial immune system algorithm |
author |
Leão, Fábio Bertequini [UNESP] |
author_facet |
Leão, Fábio Bertequini [UNESP] Pereira, Rodrigo A. F. [UNESP] Mantovani, José R. S. [UNESP] |
author_role |
author |
author2 |
Pereira, Rodrigo A. F. [UNESP] Mantovani, José R. S. [UNESP] |
author2_role |
author author |
dc.contributor.none.fl_str_mv |
Universidade Estadual Paulista (UNESP) |
dc.contributor.author.fl_str_mv |
Leão, Fábio Bertequini [UNESP] Pereira, Rodrigo A. F. [UNESP] Mantovani, José R. S. [UNESP] |
dc.subject.por.fl_str_mv |
Artificial immune systems Fault section estimation Power system protection |
topic |
Artificial immune systems Fault section estimation Power system protection |
description |
This work proposes an unconstrained binary programming (UBP) model for fault section estimation in power systems. UBP model consists in a set of equations that represent in a logical way the expected states of the relays of the apparatus protection system. An artificial immune system algorithm (AISA) is developed in order to find the correct fault section estimate provided by the data from the supervisory control and data acquisition (SCADA) system. The proposed methodology is tested using part of the South-Brazilian electric power system. Control parameters of the AISA are calibrated to increase the efficiency and velocity of the algorithm. Results show the potential and the efficiency of the proposed methodology to fault section estimation online in electric power systems. |
publishDate |
2008 |
dc.date.none.fl_str_mv |
2008-01-01 2022-04-29T07:26:29Z 2022-04-29T07:26:29Z |
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 |
16th Power Systems Computation Conference, PSCC 2008. http://hdl.handle.net/11449/228053 2-s2.0-84944097046 |
identifier_str_mv |
16th Power Systems Computation Conference, PSCC 2008. 2-s2.0-84944097046 |
url |
http://hdl.handle.net/11449/228053 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
16th Power Systems Computation Conference, PSCC 2008 |
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_ |
1803046654074421248 |