Optimal phasor measurement units placement for fault location on overhead electric power distribution feeders
Autor(a) principal: | |
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Data de Publicação: | 2011 |
Outros Autores: | , |
Tipo de documento: | Artigo de conferência |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UNESP |
Texto Completo: | http://dx.doi.org/10.1109/TDC-LA.2010.5762858 http://hdl.handle.net/11449/72441 |
Resumo: | This paper proposes a new approach for optimal phasor measurement units placement for fault location on electric power distribution systems using Greedy Randomized Adaptive Search Procedure metaheuristic and Monte Carlo simulation. The optimized placement model herein proposed is a general methodology that can be used to place devices aiming to record the voltage sag magnitudes for any fault location algorithm that uses voltage information measured at a limited set of nodes along the feeder. An overhead, three-phase, three-wire, 13.8 kV, 134-node, real-life feeder model is used to evaluate the algorithm. Tests show that the results of the fault location methodology were improved thanks to the new optimized allocation of the meters pinpointed using this methodology. © 2011 IEEE. |
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Repositório Institucional da UNESP |
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Optimal phasor measurement units placement for fault location on overhead electric power distribution feedersfault locationMonte Carlo methods and optimization methodsOptimal allocationphasor measurement units (PMUs)Electric powerElectric power distribution systemsFault locationFault location algorithmsGeneral methodologiesGreedy randomized adaptive search procedureMetaheuristicMonte Carlo SimulationOptimized allocationPhasor measurement unitPlacement modelVoltage sagsAlgorithmsComputer simulationElectric load distributionElectric power distributionElectric power system interconnectionElectric power transmissionFeedingOptimizationPhase measurementThermoelectric equipmentUnits of measurementMonte Carlo methodsThis paper proposes a new approach for optimal phasor measurement units placement for fault location on electric power distribution systems using Greedy Randomized Adaptive Search Procedure metaheuristic and Monte Carlo simulation. The optimized placement model herein proposed is a general methodology that can be used to place devices aiming to record the voltage sag magnitudes for any fault location algorithm that uses voltage information measured at a limited set of nodes along the feeder. An overhead, three-phase, three-wire, 13.8 kV, 134-node, real-life feeder model is used to evaluate the algorithm. Tests show that the results of the fault location methodology were improved thanks to the new optimized allocation of the meters pinpointed using this methodology. © 2011 IEEE.UNESP-Univ. Estadual Paulista FEIS Electrical Engineering Department, Ilha Solteira, São Paulo, 15385-000UNESP-Univ. Estadual Paulista FEIS Electrical Engineering Department, Ilha Solteira, São Paulo, 15385-000Universidade Estadual Paulista (Unesp)Bíscaro, A. A P [UNESP]Pereira, R. A F [UNESP]Mantovani, J. R S [UNESP]2014-05-27T11:25:53Z2014-05-27T11:25:53Z2011-05-31info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/conferenceObject37-43http://dx.doi.org/10.1109/TDC-LA.2010.57628582010 IEEE/PES Transmission and Distribution Conference and Exposition: Latin America, T and D-LA 2010, p. 37-43.http://hdl.handle.net/11449/7244110.1109/TDC-LA.2010.57628582-s2.0-799575486510614021283361265Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPeng2010 IEEE/PES Transmission and Distribution Conference and Exposition: Latin America, T and D-LA 2010info:eu-repo/semantics/openAccess2024-07-04T19:11:21Zoai:repositorio.unesp.br:11449/72441Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T15:07:41.629172Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false |
dc.title.none.fl_str_mv |
Optimal phasor measurement units placement for fault location on overhead electric power distribution feeders |
title |
Optimal phasor measurement units placement for fault location on overhead electric power distribution feeders |
spellingShingle |
Optimal phasor measurement units placement for fault location on overhead electric power distribution feeders Bíscaro, A. A P [UNESP] fault location Monte Carlo methods and optimization methods Optimal allocation phasor measurement units (PMUs) Electric power Electric power distribution systems Fault location Fault location algorithms General methodologies Greedy randomized adaptive search procedure Metaheuristic Monte Carlo Simulation Optimized allocation Phasor measurement unit Placement model Voltage sags Algorithms Computer simulation Electric load distribution Electric power distribution Electric power system interconnection Electric power transmission Feeding Optimization Phase measurement Thermoelectric equipment Units of measurement Monte Carlo methods |
title_short |
Optimal phasor measurement units placement for fault location on overhead electric power distribution feeders |
title_full |
Optimal phasor measurement units placement for fault location on overhead electric power distribution feeders |
title_fullStr |
Optimal phasor measurement units placement for fault location on overhead electric power distribution feeders |
title_full_unstemmed |
Optimal phasor measurement units placement for fault location on overhead electric power distribution feeders |
title_sort |
Optimal phasor measurement units placement for fault location on overhead electric power distribution feeders |
author |
Bíscaro, A. A P [UNESP] |
author_facet |
Bíscaro, A. A P [UNESP] Pereira, R. A F [UNESP] Mantovani, J. R S [UNESP] |
author_role |
author |
author2 |
Pereira, R. A F [UNESP] Mantovani, J. R S [UNESP] |
author2_role |
author author |
dc.contributor.none.fl_str_mv |
Universidade Estadual Paulista (Unesp) |
dc.contributor.author.fl_str_mv |
Bíscaro, A. A P [UNESP] Pereira, R. A F [UNESP] Mantovani, J. R S [UNESP] |
dc.subject.por.fl_str_mv |
fault location Monte Carlo methods and optimization methods Optimal allocation phasor measurement units (PMUs) Electric power Electric power distribution systems Fault location Fault location algorithms General methodologies Greedy randomized adaptive search procedure Metaheuristic Monte Carlo Simulation Optimized allocation Phasor measurement unit Placement model Voltage sags Algorithms Computer simulation Electric load distribution Electric power distribution Electric power system interconnection Electric power transmission Feeding Optimization Phase measurement Thermoelectric equipment Units of measurement Monte Carlo methods |
topic |
fault location Monte Carlo methods and optimization methods Optimal allocation phasor measurement units (PMUs) Electric power Electric power distribution systems Fault location Fault location algorithms General methodologies Greedy randomized adaptive search procedure Metaheuristic Monte Carlo Simulation Optimized allocation Phasor measurement unit Placement model Voltage sags Algorithms Computer simulation Electric load distribution Electric power distribution Electric power system interconnection Electric power transmission Feeding Optimization Phase measurement Thermoelectric equipment Units of measurement Monte Carlo methods |
description |
This paper proposes a new approach for optimal phasor measurement units placement for fault location on electric power distribution systems using Greedy Randomized Adaptive Search Procedure metaheuristic and Monte Carlo simulation. The optimized placement model herein proposed is a general methodology that can be used to place devices aiming to record the voltage sag magnitudes for any fault location algorithm that uses voltage information measured at a limited set of nodes along the feeder. An overhead, three-phase, three-wire, 13.8 kV, 134-node, real-life feeder model is used to evaluate the algorithm. Tests show that the results of the fault location methodology were improved thanks to the new optimized allocation of the meters pinpointed using this methodology. © 2011 IEEE. |
publishDate |
2011 |
dc.date.none.fl_str_mv |
2011-05-31 2014-05-27T11:25:53Z 2014-05-27T11:25:53Z |
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 |
http://dx.doi.org/10.1109/TDC-LA.2010.5762858 2010 IEEE/PES Transmission and Distribution Conference and Exposition: Latin America, T and D-LA 2010, p. 37-43. http://hdl.handle.net/11449/72441 10.1109/TDC-LA.2010.5762858 2-s2.0-79957548651 0614021283361265 |
url |
http://dx.doi.org/10.1109/TDC-LA.2010.5762858 http://hdl.handle.net/11449/72441 |
identifier_str_mv |
2010 IEEE/PES Transmission and Distribution Conference and Exposition: Latin America, T and D-LA 2010, p. 37-43. 10.1109/TDC-LA.2010.5762858 2-s2.0-79957548651 0614021283361265 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
2010 IEEE/PES Transmission and Distribution Conference and Exposition: Latin America, T and D-LA 2010 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
37-43 |
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_ |
1808128465166139392 |