Optimal subtransmission switching using a reliability simulation-based multi-objective optimization model

Detalhes bibliográficos
Autor(a) principal: Sergio, Zambrano-Asanza [UNESP]
Data de Publicação: 2022
Outros Autores: Tatiana, Proano Barros, Stalin, Banegas Dutan, Edwin, Lema Guaman, Fredy, Franco John [UNESP]
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Institucional da UNESP
Texto Completo: http://dx.doi.org/10.1016/j.epsr.2022.108068
http://hdl.handle.net/11449/240084
Resumo: The growth of subtransmission network aims at satisfying load growth, maintaining a contingency level, and providing a high quality and reliable electricity service. Utilities direct the investments to reinforce this system and thus a meshed network with multiple-point feeding to the transmission system arises. At this point, an efficient alternative to achieve these objectives is to carry out a diagnosis of the network architecture and, taking advantage of the switching capability, to plan the switching of the subtransmission lines. An optimal subtransmission switching approach is proposed based on constrained multi-objective optimization that deals with energy losses and reliability, in addition to using information on the characteristics of loads and generation. A simulation-based optimization framework is constructed using the non-dominated genetic classification algorithm NSGA-II in the optimization phase and reliability assessment during simulation phase. As a result, a set of non-dominated solutions approximating the Pareto front is obtained, which allows the planner to make decisions based on its priorities and needs. The performance of the proposal is assessed with a real subtransmission system of an Ecuadorian power utility. This approach to the operational planning of a meshed subtransmission network constitutes a powerful decision-making tool that could be adopted by distribution utilities.
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spelling Optimal subtransmission switching using a reliability simulation-based multi-objective optimization modelDistribution planningNSGA-II, optimal switchingreliabilitysubtransmission systemThe growth of subtransmission network aims at satisfying load growth, maintaining a contingency level, and providing a high quality and reliable electricity service. Utilities direct the investments to reinforce this system and thus a meshed network with multiple-point feeding to the transmission system arises. At this point, an efficient alternative to achieve these objectives is to carry out a diagnosis of the network architecture and, taking advantage of the switching capability, to plan the switching of the subtransmission lines. An optimal subtransmission switching approach is proposed based on constrained multi-objective optimization that deals with energy losses and reliability, in addition to using information on the characteristics of loads and generation. A simulation-based optimization framework is constructed using the non-dominated genetic classification algorithm NSGA-II in the optimization phase and reliability assessment during simulation phase. As a result, a set of non-dominated solutions approximating the Pareto front is obtained, which allows the planner to make decisions based on its priorities and needs. The performance of the proposal is assessed with a real subtransmission system of an Ecuadorian power utility. This approach to the operational planning of a meshed subtransmission network constitutes a powerful decision-making tool that could be adopted by distribution utilities.Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Department of Electrical Engineering São Paulo State University – UNESP, SPDepartment of Planning CENTROSUR Electric Distribution UtilitySchool of Electrical Engineering University of CuencaSchool of Energy Engineering São Paulo State University – UNESPDepartment of Electrical Engineering São Paulo State University – UNESP, SPSchool of Energy Engineering São Paulo State University – UNESPFAPESP: 2015/21972-6FAPESP: 2017/02831-8Universidade Estadual Paulista (UNESP)CENTROSUR Electric Distribution UtilityUniversity of CuencaSergio, Zambrano-Asanza [UNESP]Tatiana, Proano BarrosStalin, Banegas DutanEdwin, Lema GuamanFredy, Franco John [UNESP]2023-03-01T20:00:49Z2023-03-01T20:00:49Z2022-09-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlehttp://dx.doi.org/10.1016/j.epsr.2022.108068Electric Power Systems Research, v. 210.0378-7796http://hdl.handle.net/11449/24008410.1016/j.epsr.2022.1080682-s2.0-85130379388Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengElectric Power Systems Researchinfo:eu-repo/semantics/openAccess2023-03-01T20:00:49Zoai:repositorio.unesp.br:11449/240084Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462023-03-01T20:00:49Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false
dc.title.none.fl_str_mv Optimal subtransmission switching using a reliability simulation-based multi-objective optimization model
title Optimal subtransmission switching using a reliability simulation-based multi-objective optimization model
spellingShingle Optimal subtransmission switching using a reliability simulation-based multi-objective optimization model
Sergio, Zambrano-Asanza [UNESP]
Distribution planning
NSGA-II, optimal switching
reliability
subtransmission system
title_short Optimal subtransmission switching using a reliability simulation-based multi-objective optimization model
title_full Optimal subtransmission switching using a reliability simulation-based multi-objective optimization model
title_fullStr Optimal subtransmission switching using a reliability simulation-based multi-objective optimization model
title_full_unstemmed Optimal subtransmission switching using a reliability simulation-based multi-objective optimization model
title_sort Optimal subtransmission switching using a reliability simulation-based multi-objective optimization model
author Sergio, Zambrano-Asanza [UNESP]
author_facet Sergio, Zambrano-Asanza [UNESP]
Tatiana, Proano Barros
Stalin, Banegas Dutan
Edwin, Lema Guaman
Fredy, Franco John [UNESP]
author_role author
author2 Tatiana, Proano Barros
Stalin, Banegas Dutan
Edwin, Lema Guaman
Fredy, Franco John [UNESP]
author2_role author
author
author
author
dc.contributor.none.fl_str_mv Universidade Estadual Paulista (UNESP)
CENTROSUR Electric Distribution Utility
University of Cuenca
dc.contributor.author.fl_str_mv Sergio, Zambrano-Asanza [UNESP]
Tatiana, Proano Barros
Stalin, Banegas Dutan
Edwin, Lema Guaman
Fredy, Franco John [UNESP]
dc.subject.por.fl_str_mv Distribution planning
NSGA-II, optimal switching
reliability
subtransmission system
topic Distribution planning
NSGA-II, optimal switching
reliability
subtransmission system
description The growth of subtransmission network aims at satisfying load growth, maintaining a contingency level, and providing a high quality and reliable electricity service. Utilities direct the investments to reinforce this system and thus a meshed network with multiple-point feeding to the transmission system arises. At this point, an efficient alternative to achieve these objectives is to carry out a diagnosis of the network architecture and, taking advantage of the switching capability, to plan the switching of the subtransmission lines. An optimal subtransmission switching approach is proposed based on constrained multi-objective optimization that deals with energy losses and reliability, in addition to using information on the characteristics of loads and generation. A simulation-based optimization framework is constructed using the non-dominated genetic classification algorithm NSGA-II in the optimization phase and reliability assessment during simulation phase. As a result, a set of non-dominated solutions approximating the Pareto front is obtained, which allows the planner to make decisions based on its priorities and needs. The performance of the proposal is assessed with a real subtransmission system of an Ecuadorian power utility. This approach to the operational planning of a meshed subtransmission network constitutes a powerful decision-making tool that could be adopted by distribution utilities.
publishDate 2022
dc.date.none.fl_str_mv 2022-09-01
2023-03-01T20:00:49Z
2023-03-01T20:00:49Z
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://dx.doi.org/10.1016/j.epsr.2022.108068
Electric Power Systems Research, v. 210.
0378-7796
http://hdl.handle.net/11449/240084
10.1016/j.epsr.2022.108068
2-s2.0-85130379388
url http://dx.doi.org/10.1016/j.epsr.2022.108068
http://hdl.handle.net/11449/240084
identifier_str_mv Electric Power Systems Research, v. 210.
0378-7796
10.1016/j.epsr.2022.108068
2-s2.0-85130379388
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Electric Power Systems Research
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
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