A Stochastic Model for Medium-Term Distribution System Planning Considering CO2 Emissions

Detalhes bibliográficos
Autor(a) principal: Mejia, Mario A. [UNESP]
Data de Publicação: 2020
Outros Autores: Macedo, Leonardo H. [UNESP], Munoz-Delgado, Gregorio, Contreras, Javier, Padilha-Feltrin, Antonio [UNESP], IEEE
Tipo de documento: Artigo de conferência
Idioma: eng
Título da fonte: Repositório Institucional da UNESP
Texto Completo: http://hdl.handle.net/11449/218714
Resumo: This paper presents a new two-stage stochastic mixed-integer linear programming model for the medium-term expansion planning of power distribution systems considering the uncertainty associated with renewable energy sources, demand, and energy prices at substations. Investment decisions comprise the installation of both 1) classical alternatives such as conductors, capacitor banks, and voltage regulators, and 2) modern alternatives such as renewable distributed generation and energy storage units. Moreover, unlike conventional planning models, the proposed approach includes a voltage-dependent load representation. The proposed model aims to find a planning strategy that minimizes the investment and operating costs while meeting network operational constraints and CO2 emissions requirements. Tests are carried out with a 69-node distribution system and the results demonstrate the effectiveness and applicability of this model as an effective means of promoting an efficient, sustainable, and environmentally-friendly network.
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spelling A Stochastic Model for Medium-Term Distribution System Planning Considering CO2 EmissionsDistribution system planningrenewable energy sourcesstochastic programmingvoltage-dependent modelsThis paper presents a new two-stage stochastic mixed-integer linear programming model for the medium-term expansion planning of power distribution systems considering the uncertainty associated with renewable energy sources, demand, and energy prices at substations. Investment decisions comprise the installation of both 1) classical alternatives such as conductors, capacitor banks, and voltage regulators, and 2) modern alternatives such as renewable distributed generation and energy storage units. Moreover, unlike conventional planning models, the proposed approach includes a voltage-dependent load representation. The proposed model aims to find a planning strategy that minimizes the investment and operating costs while meeting network operational constraints and CO2 emissions requirements. Tests are carried out with a 69-node distribution system and the results demonstrate the effectiveness and applicability of this model as an effective means of promoting an efficient, sustainable, and environmentally-friendly network.Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Ministry of Science, Innovation and Universities of SpainUniversidad de Castilla-La ManchaSao Paulo State Univ, Dept Elect Engn, Ilha Solteira, BrazilUniv Castilla La Mancha, Escuela Tecn Super Ingn Ind, Ciudad Real, SpainSao Paulo State Univ, Dept Elect Engn, Ilha Solteira, BrazilCAPES: 001CAPES: 88887.371636/2019-00FAPESP: 2015/21972-6FAPESP: 2018/20355-1FAPESP: 2019/19632-3Ministry of Science, Innovation and Universities of Spain: RTI2018-096108-A-I00Ministry of Science, Innovation and Universities of Spain: RTI2018-098703-B-I00Universidad de Castilla-La Mancha: 2020-GRIN-29009IeeeUniversidade Estadual Paulista (UNESP)Univ Castilla La ManchaMejia, Mario A. [UNESP]Macedo, Leonardo H. [UNESP]Munoz-Delgado, GregorioContreras, JavierPadilha-Feltrin, Antonio [UNESP]IEEE2022-04-28T17:22:38Z2022-04-28T17:22:38Z2020-01-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/conferenceObject62020 International Conference On Smart Energy Systems And Technologies (sest). New York: Ieee, 6 p., 2020.http://hdl.handle.net/11449/218714WOS:000722591200098Web of Sciencereponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPeng2020 International Conference On Smart Energy Systems And Technologies (sest)info:eu-repo/semantics/openAccess2022-04-28T17:22:38Zoai:repositorio.unesp.br:11449/218714Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462022-04-28T17:22:38Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false
dc.title.none.fl_str_mv A Stochastic Model for Medium-Term Distribution System Planning Considering CO2 Emissions
title A Stochastic Model for Medium-Term Distribution System Planning Considering CO2 Emissions
spellingShingle A Stochastic Model for Medium-Term Distribution System Planning Considering CO2 Emissions
Mejia, Mario A. [UNESP]
Distribution system planning
renewable energy sources
stochastic programming
voltage-dependent models
title_short A Stochastic Model for Medium-Term Distribution System Planning Considering CO2 Emissions
title_full A Stochastic Model for Medium-Term Distribution System Planning Considering CO2 Emissions
title_fullStr A Stochastic Model for Medium-Term Distribution System Planning Considering CO2 Emissions
title_full_unstemmed A Stochastic Model for Medium-Term Distribution System Planning Considering CO2 Emissions
title_sort A Stochastic Model for Medium-Term Distribution System Planning Considering CO2 Emissions
author Mejia, Mario A. [UNESP]
author_facet Mejia, Mario A. [UNESP]
Macedo, Leonardo H. [UNESP]
Munoz-Delgado, Gregorio
Contreras, Javier
Padilha-Feltrin, Antonio [UNESP]
IEEE
author_role author
author2 Macedo, Leonardo H. [UNESP]
Munoz-Delgado, Gregorio
Contreras, Javier
Padilha-Feltrin, Antonio [UNESP]
IEEE
author2_role author
author
author
author
author
dc.contributor.none.fl_str_mv Universidade Estadual Paulista (UNESP)
Univ Castilla La Mancha
dc.contributor.author.fl_str_mv Mejia, Mario A. [UNESP]
Macedo, Leonardo H. [UNESP]
Munoz-Delgado, Gregorio
Contreras, Javier
Padilha-Feltrin, Antonio [UNESP]
IEEE
dc.subject.por.fl_str_mv Distribution system planning
renewable energy sources
stochastic programming
voltage-dependent models
topic Distribution system planning
renewable energy sources
stochastic programming
voltage-dependent models
description This paper presents a new two-stage stochastic mixed-integer linear programming model for the medium-term expansion planning of power distribution systems considering the uncertainty associated with renewable energy sources, demand, and energy prices at substations. Investment decisions comprise the installation of both 1) classical alternatives such as conductors, capacitor banks, and voltage regulators, and 2) modern alternatives such as renewable distributed generation and energy storage units. Moreover, unlike conventional planning models, the proposed approach includes a voltage-dependent load representation. The proposed model aims to find a planning strategy that minimizes the investment and operating costs while meeting network operational constraints and CO2 emissions requirements. Tests are carried out with a 69-node distribution system and the results demonstrate the effectiveness and applicability of this model as an effective means of promoting an efficient, sustainable, and environmentally-friendly network.
publishDate 2020
dc.date.none.fl_str_mv 2020-01-01
2022-04-28T17:22:38Z
2022-04-28T17:22:38Z
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 2020 International Conference On Smart Energy Systems And Technologies (sest). New York: Ieee, 6 p., 2020.
http://hdl.handle.net/11449/218714
WOS:000722591200098
identifier_str_mv 2020 International Conference On Smart Energy Systems And Technologies (sest). New York: Ieee, 6 p., 2020.
WOS:000722591200098
url http://hdl.handle.net/11449/218714
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 2020 International Conference On Smart Energy Systems And Technologies (sest)
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv 6
dc.publisher.none.fl_str_mv Ieee
publisher.none.fl_str_mv Ieee
dc.source.none.fl_str_mv Web of Science
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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