Automated Switch Placement in Power Distribution Systems: Analysis of Binary PSO Parameters

Detalhes bibliográficos
Autor(a) principal: Carneiro, Carlos Alberto [UNESP]
Data de Publicação: 2022
Outros Autores: Rossi, Andre Luis Debiaso [UNESP], Cebrian, Juan Carlos [UNESP], Morales-Paredes, Helmo Kelis [UNESP]
Tipo de documento: Artigo de conferência
Idioma: eng
Título da fonte: Repositório Institucional da UNESP
Texto Completo: http://dx.doi.org/10.1109/PMAPS53380.2022.9810640
http://hdl.handle.net/11449/242090
Resumo: Currently, electric utilities have improved their operational performance using automated switches (ASWs). These devices make it possible to transfer loads remotely, restoring energy supply to the greatest number of consumers. However, utilities do not have precise criteria to define the number of ASWs and their respective locations. This paper proposes a binary particle swarm optimization (BPSO) to explore ASW allocation alternatives seeking the best solution that minimizes the system Mean Interruption Frequency Index (SAIFI), System Mean Interruption Duration Index (SAIDI) and Unsupplied Energy (ENS). A probabilistic methodology based on Monte Carlo Simulation is proposed to estimate SAIFI, SAIDI and ENS. An analysis of the BPSO parameters, such as inertia weight (w) and acceleration coefficients (c1, c2) is performed to select values suitable for application in electrical networks. The results show that the parameters c1 and c2 between 3.0 and 3.3 and w = 1 improve the behavior of the BPSO.
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spelling Automated Switch Placement in Power Distribution Systems: Analysis of Binary PSO ParametersAutomated switch placementdistribution systemparticle swarm optimizationservice restorationCurrently, electric utilities have improved their operational performance using automated switches (ASWs). These devices make it possible to transfer loads remotely, restoring energy supply to the greatest number of consumers. However, utilities do not have precise criteria to define the number of ASWs and their respective locations. This paper proposes a binary particle swarm optimization (BPSO) to explore ASW allocation alternatives seeking the best solution that minimizes the system Mean Interruption Frequency Index (SAIFI), System Mean Interruption Duration Index (SAIDI) and Unsupplied Energy (ENS). A probabilistic methodology based on Monte Carlo Simulation is proposed to estimate SAIFI, SAIDI and ENS. An analysis of the BPSO parameters, such as inertia weight (w) and acceleration coefficients (c1, c2) is performed to select values suitable for application in electrical networks. The results show that the parameters c1 and c2 between 3.0 and 3.3 and w = 1 improve the behavior of the BPSO.São Paulo State University (UNESP) Institute of Science and TechnologySão Paulo State University (UNESP) Institute of Science and TechnologyUniversidade Estadual Paulista (UNESP)Carneiro, Carlos Alberto [UNESP]Rossi, Andre Luis Debiaso [UNESP]Cebrian, Juan Carlos [UNESP]Morales-Paredes, Helmo Kelis [UNESP]2023-03-02T08:38:09Z2023-03-02T08:38:09Z2022-01-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/conferenceObjecthttp://dx.doi.org/10.1109/PMAPS53380.2022.98106402022 17th International Conference on Probabilistic Methods Applied to Power Systems, PMAPS 2022.http://hdl.handle.net/11449/24209010.1109/PMAPS53380.2022.98106402-s2.0-85135058555Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPeng2022 17th International Conference on Probabilistic Methods Applied to Power Systems, PMAPS 2022info:eu-repo/semantics/openAccess2023-03-02T08:38:09Zoai:repositorio.unesp.br:11449/242090Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T19:26:38.422443Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false
dc.title.none.fl_str_mv Automated Switch Placement in Power Distribution Systems: Analysis of Binary PSO Parameters
title Automated Switch Placement in Power Distribution Systems: Analysis of Binary PSO Parameters
spellingShingle Automated Switch Placement in Power Distribution Systems: Analysis of Binary PSO Parameters
Carneiro, Carlos Alberto [UNESP]
Automated switch placement
distribution system
particle swarm optimization
service restoration
title_short Automated Switch Placement in Power Distribution Systems: Analysis of Binary PSO Parameters
title_full Automated Switch Placement in Power Distribution Systems: Analysis of Binary PSO Parameters
title_fullStr Automated Switch Placement in Power Distribution Systems: Analysis of Binary PSO Parameters
title_full_unstemmed Automated Switch Placement in Power Distribution Systems: Analysis of Binary PSO Parameters
title_sort Automated Switch Placement in Power Distribution Systems: Analysis of Binary PSO Parameters
author Carneiro, Carlos Alberto [UNESP]
author_facet Carneiro, Carlos Alberto [UNESP]
Rossi, Andre Luis Debiaso [UNESP]
Cebrian, Juan Carlos [UNESP]
Morales-Paredes, Helmo Kelis [UNESP]
author_role author
author2 Rossi, Andre Luis Debiaso [UNESP]
Cebrian, Juan Carlos [UNESP]
Morales-Paredes, Helmo Kelis [UNESP]
author2_role author
author
author
dc.contributor.none.fl_str_mv Universidade Estadual Paulista (UNESP)
dc.contributor.author.fl_str_mv Carneiro, Carlos Alberto [UNESP]
Rossi, Andre Luis Debiaso [UNESP]
Cebrian, Juan Carlos [UNESP]
Morales-Paredes, Helmo Kelis [UNESP]
dc.subject.por.fl_str_mv Automated switch placement
distribution system
particle swarm optimization
service restoration
topic Automated switch placement
distribution system
particle swarm optimization
service restoration
description Currently, electric utilities have improved their operational performance using automated switches (ASWs). These devices make it possible to transfer loads remotely, restoring energy supply to the greatest number of consumers. However, utilities do not have precise criteria to define the number of ASWs and their respective locations. This paper proposes a binary particle swarm optimization (BPSO) to explore ASW allocation alternatives seeking the best solution that minimizes the system Mean Interruption Frequency Index (SAIFI), System Mean Interruption Duration Index (SAIDI) and Unsupplied Energy (ENS). A probabilistic methodology based on Monte Carlo Simulation is proposed to estimate SAIFI, SAIDI and ENS. An analysis of the BPSO parameters, such as inertia weight (w) and acceleration coefficients (c1, c2) is performed to select values suitable for application in electrical networks. The results show that the parameters c1 and c2 between 3.0 and 3.3 and w = 1 improve the behavior of the BPSO.
publishDate 2022
dc.date.none.fl_str_mv 2022-01-01
2023-03-02T08:38:09Z
2023-03-02T08:38:09Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
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dc.identifier.uri.fl_str_mv http://dx.doi.org/10.1109/PMAPS53380.2022.9810640
2022 17th International Conference on Probabilistic Methods Applied to Power Systems, PMAPS 2022.
http://hdl.handle.net/11449/242090
10.1109/PMAPS53380.2022.9810640
2-s2.0-85135058555
url http://dx.doi.org/10.1109/PMAPS53380.2022.9810640
http://hdl.handle.net/11449/242090
identifier_str_mv 2022 17th International Conference on Probabilistic Methods Applied to Power Systems, PMAPS 2022.
10.1109/PMAPS53380.2022.9810640
2-s2.0-85135058555
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 2022 17th International Conference on Probabilistic Methods Applied to Power Systems, PMAPS 2022
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)
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