Optimal Distribution Systems Expansion Planning for Improving Service Restoration
Autor(a) principal: | |
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Data de Publicação: | 2018 |
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.2018.8511765 http://hdl.handle.net/11449/232822 |
Resumo: | This paper presents a mixed-integer second order cone programming model for the problem of optimal distribution systems expansion planning for improving service restoration. The objective is to obtain a network that allows the load to be restored after the occurrence of a contingency. Expansion of new substations, reinforcement of existing ones, addition and reconductoring of feeders are considered in the formulation of this problem. The objective is to find a meshed network that minimizes expansion costs, as well as the radial topologies for operation in predefined contingency scenarios that minimize the energy not supplied. The model considers the full ac power flow equations for the operation of the system. A24-node network is used to demonstrate the effectiveness of the proposed method. A comparison of the costs of the traditional planning with the costs of planning considering service restoration is carried out. |
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Repositório Institucional da UNESP |
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Optimal Distribution Systems Expansion Planning for Improving Service RestorationDistribution systems expansion planningmixed-integer second order cone programmingservice restoration.This paper presents a mixed-integer second order cone programming model for the problem of optimal distribution systems expansion planning for improving service restoration. The objective is to obtain a network that allows the load to be restored after the occurrence of a contingency. Expansion of new substations, reinforcement of existing ones, addition and reconductoring of feeders are considered in the formulation of this problem. The objective is to find a meshed network that minimizes expansion costs, as well as the radial topologies for operation in predefined contingency scenarios that minimize the energy not supplied. The model considers the full ac power flow equations for the operation of the system. A24-node network is used to demonstrate the effectiveness of the proposed method. A comparison of the costs of the traditional planning with the costs of planning considering service restoration is carried out.Department of Electrical Engineering São Paulo State UniversityGrid Operations and Planning Electric Power Research InstituteDepartment of Electrical Engineering São Paulo State UniversityUniversidade Estadual Paulista (UNESP)Electric Power Research InstituteMacedo, Leonardo H. [UNESP]Ortega-Vazquez, Miguel A.Romero, Ruben [UNESP]2022-04-30T13:09:13Z2022-04-30T13:09:13Z2018-10-26info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/conferenceObjecthttp://dx.doi.org/10.1109/TDC-LA.2018.8511765Proceedings of the 2018 IEEE PES Transmission and Distribution Conference and Exhibition - Latin America, T and D-LA 2018.http://hdl.handle.net/11449/23282210.1109/TDC-LA.2018.85117652-s2.0-85057002523Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengProceedings of the 2018 IEEE PES Transmission and Distribution Conference and Exhibition - Latin America, T and D-LA 2018info:eu-repo/semantics/openAccess2024-07-04T19:11:34Zoai:repositorio.unesp.br:11449/232822Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T18:00:22.875194Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false |
dc.title.none.fl_str_mv |
Optimal Distribution Systems Expansion Planning for Improving Service Restoration |
title |
Optimal Distribution Systems Expansion Planning for Improving Service Restoration |
spellingShingle |
Optimal Distribution Systems Expansion Planning for Improving Service Restoration Macedo, Leonardo H. [UNESP] Distribution systems expansion planning mixed-integer second order cone programming service restoration. |
title_short |
Optimal Distribution Systems Expansion Planning for Improving Service Restoration |
title_full |
Optimal Distribution Systems Expansion Planning for Improving Service Restoration |
title_fullStr |
Optimal Distribution Systems Expansion Planning for Improving Service Restoration |
title_full_unstemmed |
Optimal Distribution Systems Expansion Planning for Improving Service Restoration |
title_sort |
Optimal Distribution Systems Expansion Planning for Improving Service Restoration |
author |
Macedo, Leonardo H. [UNESP] |
author_facet |
Macedo, Leonardo H. [UNESP] Ortega-Vazquez, Miguel A. Romero, Ruben [UNESP] |
author_role |
author |
author2 |
Ortega-Vazquez, Miguel A. Romero, Ruben [UNESP] |
author2_role |
author author |
dc.contributor.none.fl_str_mv |
Universidade Estadual Paulista (UNESP) Electric Power Research Institute |
dc.contributor.author.fl_str_mv |
Macedo, Leonardo H. [UNESP] Ortega-Vazquez, Miguel A. Romero, Ruben [UNESP] |
dc.subject.por.fl_str_mv |
Distribution systems expansion planning mixed-integer second order cone programming service restoration. |
topic |
Distribution systems expansion planning mixed-integer second order cone programming service restoration. |
description |
This paper presents a mixed-integer second order cone programming model for the problem of optimal distribution systems expansion planning for improving service restoration. The objective is to obtain a network that allows the load to be restored after the occurrence of a contingency. Expansion of new substations, reinforcement of existing ones, addition and reconductoring of feeders are considered in the formulation of this problem. The objective is to find a meshed network that minimizes expansion costs, as well as the radial topologies for operation in predefined contingency scenarios that minimize the energy not supplied. The model considers the full ac power flow equations for the operation of the system. A24-node network is used to demonstrate the effectiveness of the proposed method. A comparison of the costs of the traditional planning with the costs of planning considering service restoration is carried out. |
publishDate |
2018 |
dc.date.none.fl_str_mv |
2018-10-26 2022-04-30T13:09:13Z 2022-04-30T13:09:13Z |
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.2018.8511765 Proceedings of the 2018 IEEE PES Transmission and Distribution Conference and Exhibition - Latin America, T and D-LA 2018. http://hdl.handle.net/11449/232822 10.1109/TDC-LA.2018.8511765 2-s2.0-85057002523 |
url |
http://dx.doi.org/10.1109/TDC-LA.2018.8511765 http://hdl.handle.net/11449/232822 |
identifier_str_mv |
Proceedings of the 2018 IEEE PES Transmission and Distribution Conference and Exhibition - Latin America, T and D-LA 2018. 10.1109/TDC-LA.2018.8511765 2-s2.0-85057002523 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
Proceedings of the 2018 IEEE PES Transmission and Distribution Conference and Exhibition - Latin America, T and D-LA 2018 |
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 |
|
_version_ |
1808128884199129088 |