An Optimization-Based Topology Error Detection Method for Power System State Estimation
Autor(a) principal: | |
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Data de Publicação: | 2022 |
Outros Autores: | , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/10400.22/22115 |
Resumo: | The paper presents an optimization-based method for topology error detection in power systems. The method utilizes the residual analysis in state estimation and minimization of normalized measurement residual, with the application of matrix inverse lemma. The work considers a hybrid measurement configuration, i.e., both SCADA and PMU measurements, for the test systems studied. The proposed method is implemented on the TOMLAB optimization platform under the mixed integer nonlinear programming category. The proposed method has been applied and tested on standard IEEE 14-bus and IEEE 118-bus test systems. The method is designed to be computationally efficient and produces accurate results for single topology error detection. The results from the IEEE 14-bus and IEEE 118-bus test systems have shown that the proposed method produces 100% and 94% accurate results for single topology error detection, respectively. The proposed method performs robustly with the increased measurement uncertainties and inclusion of bad data or gross errors in the measurements. The method has superiority in practical implementation over the meta-heuristics-based optimization methods. The proposed method can be easily implemented and could have potential application in the energy management systems of the power system control center. |
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An Optimization-Based Topology Error Detection Method for Power System State EstimationNetwork topologyOptimizationPhasor measurement unitsState estimationTopology error detectionThe paper presents an optimization-based method for topology error detection in power systems. The method utilizes the residual analysis in state estimation and minimization of normalized measurement residual, with the application of matrix inverse lemma. The work considers a hybrid measurement configuration, i.e., both SCADA and PMU measurements, for the test systems studied. The proposed method is implemented on the TOMLAB optimization platform under the mixed integer nonlinear programming category. The proposed method has been applied and tested on standard IEEE 14-bus and IEEE 118-bus test systems. The method is designed to be computationally efficient and produces accurate results for single topology error detection. The results from the IEEE 14-bus and IEEE 118-bus test systems have shown that the proposed method produces 100% and 94% accurate results for single topology error detection, respectively. The proposed method performs robustly with the increased measurement uncertainties and inclusion of bad data or gross errors in the measurements. The method has superiority in practical implementation over the meta-heuristics-based optimization methods. The proposed method can be easily implemented and could have potential application in the energy management systems of the power system control center.This work was supported by the Department of Science and Technology, India, and Central Power Research Institute, India under project no. DST/EE/2014250 and CPRI/EE/2014091, respectively. Joao Soares acknowledge the work facilities and equipment provided by GECAD research centre funded with FEDER Funds through COMPETE program and from National Funds through (FCT) under UIDB/00760/2020 and CEECIND/02814/2017 to execute the work.ElsevierRepositório Científico do Instituto Politécnico do PortoSrivastava, AnkurChakrabarti, SaikatSoares, JoãoSingh, Sri Niwas2023-02-02T12:39:02Z20222022-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10400.22/22115eng10.1016/j.epsr.2022.107914metadata only accessinfo:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-03-13T13:18:41Zoai:recipp.ipp.pt:10400.22/22115Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T17:42:10.201745Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse |
dc.title.none.fl_str_mv |
An Optimization-Based Topology Error Detection Method for Power System State Estimation |
title |
An Optimization-Based Topology Error Detection Method for Power System State Estimation |
spellingShingle |
An Optimization-Based Topology Error Detection Method for Power System State Estimation Srivastava, Ankur Network topology Optimization Phasor measurement units State estimation Topology error detection |
title_short |
An Optimization-Based Topology Error Detection Method for Power System State Estimation |
title_full |
An Optimization-Based Topology Error Detection Method for Power System State Estimation |
title_fullStr |
An Optimization-Based Topology Error Detection Method for Power System State Estimation |
title_full_unstemmed |
An Optimization-Based Topology Error Detection Method for Power System State Estimation |
title_sort |
An Optimization-Based Topology Error Detection Method for Power System State Estimation |
author |
Srivastava, Ankur |
author_facet |
Srivastava, Ankur Chakrabarti, Saikat Soares, João Singh, Sri Niwas |
author_role |
author |
author2 |
Chakrabarti, Saikat Soares, João Singh, Sri Niwas |
author2_role |
author author author |
dc.contributor.none.fl_str_mv |
Repositório Científico do Instituto Politécnico do Porto |
dc.contributor.author.fl_str_mv |
Srivastava, Ankur Chakrabarti, Saikat Soares, João Singh, Sri Niwas |
dc.subject.por.fl_str_mv |
Network topology Optimization Phasor measurement units State estimation Topology error detection |
topic |
Network topology Optimization Phasor measurement units State estimation Topology error detection |
description |
The paper presents an optimization-based method for topology error detection in power systems. The method utilizes the residual analysis in state estimation and minimization of normalized measurement residual, with the application of matrix inverse lemma. The work considers a hybrid measurement configuration, i.e., both SCADA and PMU measurements, for the test systems studied. The proposed method is implemented on the TOMLAB optimization platform under the mixed integer nonlinear programming category. The proposed method has been applied and tested on standard IEEE 14-bus and IEEE 118-bus test systems. The method is designed to be computationally efficient and produces accurate results for single topology error detection. The results from the IEEE 14-bus and IEEE 118-bus test systems have shown that the proposed method produces 100% and 94% accurate results for single topology error detection, respectively. The proposed method performs robustly with the increased measurement uncertainties and inclusion of bad data or gross errors in the measurements. The method has superiority in practical implementation over the meta-heuristics-based optimization methods. The proposed method can be easily implemented and could have potential application in the energy management systems of the power system control center. |
publishDate |
2022 |
dc.date.none.fl_str_mv |
2022 2022-01-01T00:00:00Z 2023-02-02T12:39:02Z |
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://hdl.handle.net/10400.22/22115 |
url |
http://hdl.handle.net/10400.22/22115 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
10.1016/j.epsr.2022.107914 |
dc.rights.driver.fl_str_mv |
metadata only access info:eu-repo/semantics/openAccess |
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metadata only access |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Elsevier |
publisher.none.fl_str_mv |
Elsevier |
dc.source.none.fl_str_mv |
reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação instacron:RCAAP |
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Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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RCAAP |
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RCAAP |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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1799131508004356096 |