A stochastic model for medium-term distribution system planning considering CO2emissions
Autor(a) principal: | |
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Data de Publicação: | 2020 |
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/SEST48500.2020.9203563 http://hdl.handle.net/11449/233049 |
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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A stochastic model for medium-term distribution system planning considering CO2emissionsDistribution 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.São Paulo State University Department of Electrical EngineeringUniversidad de Castilla-La Mancha Escuela Técnica Superior de Ingenieriá IndustrialSão Paulo State University Department of Electrical EngineeringUniversidade Estadual Paulista (UNESP)Escuela Técnica Superior de Ingenieriá IndustrialMejia, Mario A. [UNESP]Macedo, Leonardo H. [UNESP]Munoz-Delgado, GregorioContreras, JavierPadilha-Feltrin, Antonio [UNESP]2022-05-01T00:57:50Z2022-05-01T00:57:50Z2020-09-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/conferenceObjecthttp://dx.doi.org/10.1109/SEST48500.2020.9203563SEST 2020 - 3rd International Conference on Smart Energy Systems and Technologies.http://hdl.handle.net/11449/23304910.1109/SEST48500.2020.92035632-s2.0-85093650379Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengSEST 2020 - 3rd International Conference on Smart Energy Systems and Technologiesinfo:eu-repo/semantics/openAccess2024-07-04T19:11:39Zoai:repositorio.unesp.br:11449/233049Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T19:00:06.946513Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false |
dc.title.none.fl_str_mv |
A stochastic model for medium-term distribution system planning considering CO2emissions |
title |
A stochastic model for medium-term distribution system planning considering CO2emissions |
spellingShingle |
A stochastic model for medium-term distribution system planning considering CO2emissions 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 CO2emissions |
title_full |
A stochastic model for medium-term distribution system planning considering CO2emissions |
title_fullStr |
A stochastic model for medium-term distribution system planning considering CO2emissions |
title_full_unstemmed |
A stochastic model for medium-term distribution system planning considering CO2emissions |
title_sort |
A stochastic model for medium-term distribution system planning considering CO2emissions |
author |
Mejia, Mario A. [UNESP] |
author_facet |
Mejia, Mario A. [UNESP] Macedo, Leonardo H. [UNESP] Munoz-Delgado, Gregorio Contreras, Javier Padilha-Feltrin, Antonio [UNESP] |
author_role |
author |
author2 |
Macedo, Leonardo H. [UNESP] Munoz-Delgado, Gregorio Contreras, Javier Padilha-Feltrin, Antonio [UNESP] |
author2_role |
author author author author |
dc.contributor.none.fl_str_mv |
Universidade Estadual Paulista (UNESP) Escuela Técnica Superior de Ingenieriá Industrial |
dc.contributor.author.fl_str_mv |
Mejia, Mario A. [UNESP] Macedo, Leonardo H. [UNESP] Munoz-Delgado, Gregorio Contreras, Javier Padilha-Feltrin, Antonio [UNESP] |
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 |
2020-09-01 2022-05-01T00:57:50Z 2022-05-01T00:57:50Z |
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/SEST48500.2020.9203563 SEST 2020 - 3rd International Conference on Smart Energy Systems and Technologies. http://hdl.handle.net/11449/233049 10.1109/SEST48500.2020.9203563 2-s2.0-85093650379 |
url |
http://dx.doi.org/10.1109/SEST48500.2020.9203563 http://hdl.handle.net/11449/233049 |
identifier_str_mv |
SEST 2020 - 3rd International Conference on Smart Energy Systems and Technologies. 10.1109/SEST48500.2020.9203563 2-s2.0-85093650379 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
SEST 2020 - 3rd International Conference on Smart Energy Systems and Technologies |
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_ |
1808129010744426496 |