Allocation of distributed generation to minimize losses in the distribution power system

Detalhes bibliográficos
Autor(a) principal: Serrano, Hugo De Oliveira Motta [UNESP]
Data de Publicação: 2021
Outros Autores: Leite, Jonatas Boas [UNESP]
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.
id UNSP_aa8d16b045486adbd54ed263946feb0a
oai_identifier_str oai:repositorio.unesp.br:11449/222696
network_acronym_str UNSP
network_name_str Repositório Institucional da UNESP
repository_id_str 2946
spelling 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:29462022-04-28T19:46:08Repositório 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_ 1803047346452299776

Registros relacionados