Increasing distributed generation hosting capacity in distribution systems via optimal coordination of electric vehicle aggregators

Detalhes bibliográficos
Autor(a) principal: Quijano, Darwin A. [UNESP]
Data de Publicação: 2021
Outros Autores: Melgar-Dominguez, Ozy D. [UNESP], Sabillon, Carlos, Venkatesh, Bala, Padilha-Feltrin, Antonio [UNESP]
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Institucional da UNESP
Texto Completo: http://dx.doi.org/10.1049/gtd2.12026
http://hdl.handle.net/11449/208740
Resumo: This work presents a novel strategy, designed from the distribution system operator viewpoint, aimed at estimating the hosting capacity in electric distribution systems when controllable plug-in electric vehicles are in place. The strategy seeks to determine the maximum wind-based distributed generation penetration by coordinating, on a forecast basis, the dispatch of electric vehicle aggregators, the operation of voltage regulation devices, and the active and reactive distributed generation power injections. Different from previous works, the proposed approach leverages controllable features of electric vehicles taking into account technical electric vehicle characteristics, driving behaviour of electric vehicle owners, and electric vehicle energy requirements to accomplish their primary purpose. The presented strategy is formulated as a two-stage stochastic mixed-integer linear programming problem. The first stage maximises the distributed generation installed capacity, while the second stage minimises the energy losses during the planning horizon. Probability density functions are used to describe the uncertainties associated with renewable distributed generation, conventional demand, and electric vehicle driving patterns. Obtained results show that controlling the power dispatched to electric vehicle aggregators can increase the distributed generation hosting capacity by up to 15% (given a 40% electric vehicle penetration), when compared to an uncontrolled electric vehicle approach.
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spelling Increasing distributed generation hosting capacity in distribution systems via optimal coordination of electric vehicle aggregatorsThis work presents a novel strategy, designed from the distribution system operator viewpoint, aimed at estimating the hosting capacity in electric distribution systems when controllable plug-in electric vehicles are in place. The strategy seeks to determine the maximum wind-based distributed generation penetration by coordinating, on a forecast basis, the dispatch of electric vehicle aggregators, the operation of voltage regulation devices, and the active and reactive distributed generation power injections. Different from previous works, the proposed approach leverages controllable features of electric vehicles taking into account technical electric vehicle characteristics, driving behaviour of electric vehicle owners, and electric vehicle energy requirements to accomplish their primary purpose. The presented strategy is formulated as a two-stage stochastic mixed-integer linear programming problem. The first stage maximises the distributed generation installed capacity, while the second stage minimises the energy losses during the planning horizon. Probability density functions are used to describe the uncertainties associated with renewable distributed generation, conventional demand, and electric vehicle driving patterns. Obtained results show that controlling the power dispatched to electric vehicle aggregators can increase the distributed generation hosting capacity by up to 15% (given a 40% electric vehicle penetration), when compared to an uncontrolled electric vehicle approach.Electrical Engineering Department São Paulo State University (UNESP)Centre for Urban Energy Ryerson UniversityElectrical Engineering Department São Paulo State University (UNESP)Universidade Estadual Paulista (Unesp)Ryerson UniversityQuijano, Darwin A. [UNESP]Melgar-Dominguez, Ozy D. [UNESP]Sabillon, CarlosVenkatesh, BalaPadilha-Feltrin, Antonio [UNESP]2021-06-25T11:18:15Z2021-06-25T11:18:15Z2021-01-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article359-370http://dx.doi.org/10.1049/gtd2.12026IET Generation, Transmission and Distribution, v. 15, n. 2, p. 359-370, 2021.1751-86951751-8687http://hdl.handle.net/11449/20874010.1049/gtd2.120262-s2.0-85107332291Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengIET Generation, Transmission and Distributioninfo:eu-repo/semantics/openAccess2024-07-04T19:06:35Zoai:repositorio.unesp.br:11449/208740Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T20:32:41.992873Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false
dc.title.none.fl_str_mv Increasing distributed generation hosting capacity in distribution systems via optimal coordination of electric vehicle aggregators
title Increasing distributed generation hosting capacity in distribution systems via optimal coordination of electric vehicle aggregators
spellingShingle Increasing distributed generation hosting capacity in distribution systems via optimal coordination of electric vehicle aggregators
Quijano, Darwin A. [UNESP]
title_short Increasing distributed generation hosting capacity in distribution systems via optimal coordination of electric vehicle aggregators
title_full Increasing distributed generation hosting capacity in distribution systems via optimal coordination of electric vehicle aggregators
title_fullStr Increasing distributed generation hosting capacity in distribution systems via optimal coordination of electric vehicle aggregators
title_full_unstemmed Increasing distributed generation hosting capacity in distribution systems via optimal coordination of electric vehicle aggregators
title_sort Increasing distributed generation hosting capacity in distribution systems via optimal coordination of electric vehicle aggregators
author Quijano, Darwin A. [UNESP]
author_facet Quijano, Darwin A. [UNESP]
Melgar-Dominguez, Ozy D. [UNESP]
Sabillon, Carlos
Venkatesh, Bala
Padilha-Feltrin, Antonio [UNESP]
author_role author
author2 Melgar-Dominguez, Ozy D. [UNESP]
Sabillon, Carlos
Venkatesh, Bala
Padilha-Feltrin, Antonio [UNESP]
author2_role author
author
author
author
dc.contributor.none.fl_str_mv Universidade Estadual Paulista (Unesp)
Ryerson University
dc.contributor.author.fl_str_mv Quijano, Darwin A. [UNESP]
Melgar-Dominguez, Ozy D. [UNESP]
Sabillon, Carlos
Venkatesh, Bala
Padilha-Feltrin, Antonio [UNESP]
description This work presents a novel strategy, designed from the distribution system operator viewpoint, aimed at estimating the hosting capacity in electric distribution systems when controllable plug-in electric vehicles are in place. The strategy seeks to determine the maximum wind-based distributed generation penetration by coordinating, on a forecast basis, the dispatch of electric vehicle aggregators, the operation of voltage regulation devices, and the active and reactive distributed generation power injections. Different from previous works, the proposed approach leverages controllable features of electric vehicles taking into account technical electric vehicle characteristics, driving behaviour of electric vehicle owners, and electric vehicle energy requirements to accomplish their primary purpose. The presented strategy is formulated as a two-stage stochastic mixed-integer linear programming problem. The first stage maximises the distributed generation installed capacity, while the second stage minimises the energy losses during the planning horizon. Probability density functions are used to describe the uncertainties associated with renewable distributed generation, conventional demand, and electric vehicle driving patterns. Obtained results show that controlling the power dispatched to electric vehicle aggregators can increase the distributed generation hosting capacity by up to 15% (given a 40% electric vehicle penetration), when compared to an uncontrolled electric vehicle approach.
publishDate 2021
dc.date.none.fl_str_mv 2021-06-25T11:18:15Z
2021-06-25T11:18:15Z
2021-01-01
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/10.1049/gtd2.12026
IET Generation, Transmission and Distribution, v. 15, n. 2, p. 359-370, 2021.
1751-8695
1751-8687
http://hdl.handle.net/11449/208740
10.1049/gtd2.12026
2-s2.0-85107332291
url http://dx.doi.org/10.1049/gtd2.12026
http://hdl.handle.net/11449/208740
identifier_str_mv IET Generation, Transmission and Distribution, v. 15, n. 2, p. 359-370, 2021.
1751-8695
1751-8687
10.1049/gtd2.12026
2-s2.0-85107332291
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv IET Generation, Transmission and Distribution
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv 359-370
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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