Allocation of distributed generation to minimize losses in the distribution power system
Autor(a) principal: | |
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Data de Publicação: | 2021 |
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/ISGTLatinAmerica52371.2021.9543072 http://hdl.handle.net/11449/222696 |
Resumo: | Distributed generation (DG) has been increasing the electricity generation capacity around the world, becoming an area of great interest. DG benefits the distribution system by reducing losses and improving the energy quality and reliability of the system, in addition to the greenhouse gases reduction. The problem of dimensioning and allocating DGs is important since their installation in nonoptimal places can result in increased system losses and operation costs. This article presents a method for optimal allocation and dimensioning of DGs to reduce total losses in the power distribution feeders. The solution technique uses the greedy randomized adaptive search procedure together (GRASP) with tabu search. Results under a real-world distribution system shows the efficiency of the proposed methodology. |
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Allocation of distributed generation to minimize losses in the distribution power systemDistributed Generation AllocationDistribution SystemsGRASP and Tabu Search metaheuristicDistributed generation (DG) has been increasing the electricity generation capacity around the world, becoming an area of great interest. DG benefits the distribution system by reducing losses and improving the energy quality and reliability of the system, in addition to the greenhouse gases reduction. The problem of dimensioning and allocating DGs is important since their installation in nonoptimal places can result in increased system losses and operation costs. This article presents a method for optimal allocation and dimensioning of DGs to reduce total losses in the power distribution feeders. The solution technique uses the greedy randomized adaptive search procedure together (GRASP) with tabu search. Results under a real-world distribution system shows the efficiency of the proposed methodology.São Paulo State University- UNESP Electrical Engineering Department, SPSão Paulo State University- UNESP Electrical Engineering Department, SPUniversidade Estadual Paulista (UNESP)Serrano, Hugo De Oliveira Motta [UNESP]Leite, Jonatas Boas [UNESP]2022-04-28T19:46:08Z2022-04-28T19:46:08Z2021-09-15info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/conferenceObjecthttp://dx.doi.org/10.1109/ISGTLatinAmerica52371.2021.95430722021 IEEE PES Innovative Smart Grid Technologies Conference - Latin America, ISGT Latin America 2021.http://hdl.handle.net/11449/22269610.1109/ISGTLatinAmerica52371.2021.95430722-s2.0-85117570794Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPeng2021 IEEE PES Innovative Smart Grid Technologies Conference - Latin America, ISGT Latin America 2021info:eu-repo/semantics/openAccess2022-04-28T19:46:08Zoai:repositorio.unesp.br:11449/222696Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T23:07:56.574028Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false |
dc.title.none.fl_str_mv |
Allocation of distributed generation to minimize losses in the distribution power system |
title |
Allocation of distributed generation to minimize losses in the distribution power system |
spellingShingle |
Allocation of distributed generation to minimize losses in the distribution power system Serrano, Hugo De Oliveira Motta [UNESP] Distributed Generation Allocation Distribution Systems GRASP and Tabu Search metaheuristic |
title_short |
Allocation of distributed generation to minimize losses in the distribution power system |
title_full |
Allocation of distributed generation to minimize losses in the distribution power system |
title_fullStr |
Allocation of distributed generation to minimize losses in the distribution power system |
title_full_unstemmed |
Allocation of distributed generation to minimize losses in the distribution power system |
title_sort |
Allocation of distributed generation to minimize losses in the distribution power system |
author |
Serrano, Hugo De Oliveira Motta [UNESP] |
author_facet |
Serrano, Hugo De Oliveira Motta [UNESP] Leite, Jonatas Boas [UNESP] |
author_role |
author |
author2 |
Leite, Jonatas Boas [UNESP] |
author2_role |
author |
dc.contributor.none.fl_str_mv |
Universidade Estadual Paulista (UNESP) |
dc.contributor.author.fl_str_mv |
Serrano, Hugo De Oliveira Motta [UNESP] Leite, Jonatas Boas [UNESP] |
dc.subject.por.fl_str_mv |
Distributed Generation Allocation Distribution Systems GRASP and Tabu Search metaheuristic |
topic |
Distributed Generation Allocation Distribution Systems GRASP and Tabu Search metaheuristic |
description |
Distributed generation (DG) has been increasing the electricity generation capacity around the world, becoming an area of great interest. DG benefits the distribution system by reducing losses and improving the energy quality and reliability of the system, in addition to the greenhouse gases reduction. The problem of dimensioning and allocating DGs is important since their installation in nonoptimal places can result in increased system losses and operation costs. This article presents a method for optimal allocation and dimensioning of DGs to reduce total losses in the power distribution feeders. The solution technique uses the greedy randomized adaptive search procedure together (GRASP) with tabu search. Results under a real-world distribution system shows the efficiency of the proposed methodology. |
publishDate |
2021 |
dc.date.none.fl_str_mv |
2021-09-15 2022-04-28T19:46:08Z 2022-04-28T19:46:08Z |
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/ISGTLatinAmerica52371.2021.9543072 2021 IEEE PES Innovative Smart Grid Technologies Conference - Latin America, ISGT Latin America 2021. http://hdl.handle.net/11449/222696 10.1109/ISGTLatinAmerica52371.2021.9543072 2-s2.0-85117570794 |
url |
http://dx.doi.org/10.1109/ISGTLatinAmerica52371.2021.9543072 http://hdl.handle.net/11449/222696 |
identifier_str_mv |
2021 IEEE PES Innovative Smart Grid Technologies Conference - Latin America, ISGT Latin America 2021. 10.1109/ISGTLatinAmerica52371.2021.9543072 2-s2.0-85117570794 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
2021 IEEE PES Innovative Smart Grid Technologies Conference - Latin America, ISGT Latin America 2021 |
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_ |
1808129492389986304 |