An Optimization-Based Topology Error Detection Method for Power System State Estimation

Detalhes bibliográficos
Autor(a) principal: Srivastava, Ankur
Data de Publicação: 2022
Outros Autores: Chakrabarti, Saikat, Soares, João, Singh, Sri Niwas
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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spelling 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
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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
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