Short-Term Distribution System Planning Using A System Reduction Technique
Autor(a) principal: | |
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Data de Publicação: | 2021 |
Outros Autores: | , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UNESP |
Texto Completo: | http://dx.doi.org/10.1109/ACCESS.2021.3128052 http://hdl.handle.net/11449/231553 |
Resumo: | Given the necessity of developing more efficient electric distribution systems (EDSs) and providing a continuous energy service for active and passive users, distribution system planners are constantly seeking for more robust planning strategies that can address the complexities of large-scale EDSs. In this regard, the proposed work investigates the implementation of a novel strategy that is based on two stages to tackle the short-term planning problem in large-scale EDSs. In the first stage, a system reduction technique is developed to remove all non-desired buses and circuits from the original large-scale EDS, while in the second stage an optimization model is formulated to represent the EDS expansion planning problem. The planning stage is designed using a multi-period formulation, which defines, in the most cost-effective way, actions such as the allocation of voltage regulators (VRs) and capacitor banks (CBs) to improve the EDS operation, considering the demand growth and new requests for distributed generation (DG) connections. The objective function of this optimization model minimizes the expected cost of energy purchased from the market and charges due to carbon emission taxes, while the energy purchased from DG developers is maximized. For simulation purposes, a real 1080-bus EDS is reduced to an equivalent 54-bus system and implementing the developed optimization model, results show that a set of planning actions can be obtained to improve the EDS operation. These obtained planning actions are projected to the 1080-bus EDS and using an optimal power flow tool, the accuracy of the proposed planning strategy is estimated. |
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Short-Term Distribution System Planning Using A System Reduction TechniqueShort-term distribution system planningstochastic mixed-integer linear programming modelSystem reduction techniqueGiven the necessity of developing more efficient electric distribution systems (EDSs) and providing a continuous energy service for active and passive users, distribution system planners are constantly seeking for more robust planning strategies that can address the complexities of large-scale EDSs. In this regard, the proposed work investigates the implementation of a novel strategy that is based on two stages to tackle the short-term planning problem in large-scale EDSs. In the first stage, a system reduction technique is developed to remove all non-desired buses and circuits from the original large-scale EDS, while in the second stage an optimization model is formulated to represent the EDS expansion planning problem. The planning stage is designed using a multi-period formulation, which defines, in the most cost-effective way, actions such as the allocation of voltage regulators (VRs) and capacitor banks (CBs) to improve the EDS operation, considering the demand growth and new requests for distributed generation (DG) connections. The objective function of this optimization model minimizes the expected cost of energy purchased from the market and charges due to carbon emission taxes, while the energy purchased from DG developers is maximized. For simulation purposes, a real 1080-bus EDS is reduced to an equivalent 54-bus system and implementing the developed optimization model, results show that a set of planning actions can be obtained to improve the EDS operation. These obtained planning actions are projected to the 1080-bus EDS and using an optimal power flow tool, the accuracy of the proposed planning strategy is estimated.Electrical Engineering Department, São Paulo State University (UNESP), Ilha Solteira, São Paulo, Brazil.Universidade Estadual Paulista (UNESP)Melgar-Dominguez, Ozy D.Salas, Richard W.Sanches Mantovani, Jose R.2022-04-29T08:46:06Z2022-04-29T08:46:06Z2021-01-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlehttp://dx.doi.org/10.1109/ACCESS.2021.3128052IEEE Access.2169-3536http://hdl.handle.net/11449/23155310.1109/ACCESS.2021.31280522-s2.0-85119454485Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengIEEE Accessinfo:eu-repo/semantics/openAccess2024-07-04T19:06:35Zoai:repositorio.unesp.br:11449/231553Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T20:27:34.642807Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false |
dc.title.none.fl_str_mv |
Short-Term Distribution System Planning Using A System Reduction Technique |
title |
Short-Term Distribution System Planning Using A System Reduction Technique |
spellingShingle |
Short-Term Distribution System Planning Using A System Reduction Technique Melgar-Dominguez, Ozy D. Short-term distribution system planning stochastic mixed-integer linear programming model System reduction technique |
title_short |
Short-Term Distribution System Planning Using A System Reduction Technique |
title_full |
Short-Term Distribution System Planning Using A System Reduction Technique |
title_fullStr |
Short-Term Distribution System Planning Using A System Reduction Technique |
title_full_unstemmed |
Short-Term Distribution System Planning Using A System Reduction Technique |
title_sort |
Short-Term Distribution System Planning Using A System Reduction Technique |
author |
Melgar-Dominguez, Ozy D. |
author_facet |
Melgar-Dominguez, Ozy D. Salas, Richard W. Sanches Mantovani, Jose R. |
author_role |
author |
author2 |
Salas, Richard W. Sanches Mantovani, Jose R. |
author2_role |
author author |
dc.contributor.none.fl_str_mv |
Universidade Estadual Paulista (UNESP) |
dc.contributor.author.fl_str_mv |
Melgar-Dominguez, Ozy D. Salas, Richard W. Sanches Mantovani, Jose R. |
dc.subject.por.fl_str_mv |
Short-term distribution system planning stochastic mixed-integer linear programming model System reduction technique |
topic |
Short-term distribution system planning stochastic mixed-integer linear programming model System reduction technique |
description |
Given the necessity of developing more efficient electric distribution systems (EDSs) and providing a continuous energy service for active and passive users, distribution system planners are constantly seeking for more robust planning strategies that can address the complexities of large-scale EDSs. In this regard, the proposed work investigates the implementation of a novel strategy that is based on two stages to tackle the short-term planning problem in large-scale EDSs. In the first stage, a system reduction technique is developed to remove all non-desired buses and circuits from the original large-scale EDS, while in the second stage an optimization model is formulated to represent the EDS expansion planning problem. The planning stage is designed using a multi-period formulation, which defines, in the most cost-effective way, actions such as the allocation of voltage regulators (VRs) and capacitor banks (CBs) to improve the EDS operation, considering the demand growth and new requests for distributed generation (DG) connections. The objective function of this optimization model minimizes the expected cost of energy purchased from the market and charges due to carbon emission taxes, while the energy purchased from DG developers is maximized. For simulation purposes, a real 1080-bus EDS is reduced to an equivalent 54-bus system and implementing the developed optimization model, results show that a set of planning actions can be obtained to improve the EDS operation. These obtained planning actions are projected to the 1080-bus EDS and using an optimal power flow tool, the accuracy of the proposed planning strategy is estimated. |
publishDate |
2021 |
dc.date.none.fl_str_mv |
2021-01-01 2022-04-29T08:46:06Z 2022-04-29T08:46:06Z |
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/10.1109/ACCESS.2021.3128052 IEEE Access. 2169-3536 http://hdl.handle.net/11449/231553 10.1109/ACCESS.2021.3128052 2-s2.0-85119454485 |
url |
http://dx.doi.org/10.1109/ACCESS.2021.3128052 http://hdl.handle.net/11449/231553 |
identifier_str_mv |
IEEE Access. 2169-3536 10.1109/ACCESS.2021.3128052 2-s2.0-85119454485 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
IEEE Access |
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_ |
1808129204691140608 |