Environmentally committed short-term planning of electrical distribution systems considering renewable based DG siting and sizing

Detalhes bibliográficos
Autor(a) principal: Dominguez, Ozy D. Melgar [UNESP]
Data de Publicação: 2017
Outros Autores: Pourakbari-Kasmaei, Mahdi [UNESP], Mantovani, Jose Roberto Sanches [UNESP], Lavorato, Marina
Tipo de documento: Artigo de conferência
Idioma: eng
Título da fonte: Repositório Institucional da UNESP
Texto Completo: http://dx.doi.org/10.1109/EEEIC.2017.7977735
http://hdl.handle.net/11449/179075
Resumo: This paper proposes an environmentally committed mixed-integer linear programming (MILP) model to find the best plan for the electrical distribution systems (EDSs) in a short-term planning horizon. In this regard, the energy delivered by the substation and the total investment cost are minimized while the stochasticity related with the demand and photovoltaic (PV) generation is modeled via external uncertainty indexes. Considering PV generation, switchable and fixed capacitor banks (CBs), voltage regulators (VRs), conductor replacement, as well as operating costs results in a mixed-integer nonlinear programming (MINLP) model. However, to obtain the globally optimal solution, this highly nonlinear model, using appropriate linearization techniques, is recast to an MILP model. In order to validate and show the effectiveness of the proposed model, a 42-node system is considered in detail.
id UNSP_eca5d7f6f3fffd85e4a0ae0f81c8459a
oai_identifier_str oai:repositorio.unesp.br:11449/179075
network_acronym_str UNSP
network_name_str Repositório Institucional da UNESP
repository_id_str 2946
spelling Environmentally committed short-term planning of electrical distribution systems considering renewable based DG siting and sizingEnvironmentally committed planExternal uncertainty indexesMixed-integer linear programmingShort-term planningThis paper proposes an environmentally committed mixed-integer linear programming (MILP) model to find the best plan for the electrical distribution systems (EDSs) in a short-term planning horizon. In this regard, the energy delivered by the substation and the total investment cost are minimized while the stochasticity related with the demand and photovoltaic (PV) generation is modeled via external uncertainty indexes. Considering PV generation, switchable and fixed capacitor banks (CBs), voltage regulators (VRs), conductor replacement, as well as operating costs results in a mixed-integer nonlinear programming (MINLP) model. However, to obtain the globally optimal solution, this highly nonlinear model, using appropriate linearization techniques, is recast to an MILP model. In order to validate and show the effectiveness of the proposed model, a 42-node system is considered in detail.Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)Dept. of Electrical Engineering UNESPElectrical Engineering Faculty PUC-CampinasDept. of Electrical Engineering UNESPUniversidade Estadual Paulista (Unesp)PUC-CampinasDominguez, Ozy D. Melgar [UNESP]Pourakbari-Kasmaei, Mahdi [UNESP]Mantovani, Jose Roberto Sanches [UNESP]Lavorato, Marina2018-12-11T17:33:27Z2018-12-11T17:33:27Z2017-07-12info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/conferenceObjecthttp://dx.doi.org/10.1109/EEEIC.2017.7977735Conference Proceedings - 2017 17th IEEE International Conference on Environment and Electrical Engineering and 2017 1st IEEE Industrial and Commercial Power Systems Europe, EEEIC / I and CPS Europe 2017.http://hdl.handle.net/11449/17907510.1109/EEEIC.2017.79777352-s2.0-85026770512Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengConference Proceedings - 2017 17th IEEE International Conference on Environment and Electrical Engineering and 2017 1st IEEE Industrial and Commercial Power Systems Europe, EEEIC / I and CPS Europe 2017info:eu-repo/semantics/openAccess2021-10-23T21:47:01Zoai:repositorio.unesp.br:11449/179075Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462021-10-23T21:47:01Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false
dc.title.none.fl_str_mv Environmentally committed short-term planning of electrical distribution systems considering renewable based DG siting and sizing
title Environmentally committed short-term planning of electrical distribution systems considering renewable based DG siting and sizing
spellingShingle Environmentally committed short-term planning of electrical distribution systems considering renewable based DG siting and sizing
Dominguez, Ozy D. Melgar [UNESP]
Environmentally committed plan
External uncertainty indexes
Mixed-integer linear programming
Short-term planning
title_short Environmentally committed short-term planning of electrical distribution systems considering renewable based DG siting and sizing
title_full Environmentally committed short-term planning of electrical distribution systems considering renewable based DG siting and sizing
title_fullStr Environmentally committed short-term planning of electrical distribution systems considering renewable based DG siting and sizing
title_full_unstemmed Environmentally committed short-term planning of electrical distribution systems considering renewable based DG siting and sizing
title_sort Environmentally committed short-term planning of electrical distribution systems considering renewable based DG siting and sizing
author Dominguez, Ozy D. Melgar [UNESP]
author_facet Dominguez, Ozy D. Melgar [UNESP]
Pourakbari-Kasmaei, Mahdi [UNESP]
Mantovani, Jose Roberto Sanches [UNESP]
Lavorato, Marina
author_role author
author2 Pourakbari-Kasmaei, Mahdi [UNESP]
Mantovani, Jose Roberto Sanches [UNESP]
Lavorato, Marina
author2_role author
author
author
dc.contributor.none.fl_str_mv Universidade Estadual Paulista (Unesp)
PUC-Campinas
dc.contributor.author.fl_str_mv Dominguez, Ozy D. Melgar [UNESP]
Pourakbari-Kasmaei, Mahdi [UNESP]
Mantovani, Jose Roberto Sanches [UNESP]
Lavorato, Marina
dc.subject.por.fl_str_mv Environmentally committed plan
External uncertainty indexes
Mixed-integer linear programming
Short-term planning
topic Environmentally committed plan
External uncertainty indexes
Mixed-integer linear programming
Short-term planning
description This paper proposes an environmentally committed mixed-integer linear programming (MILP) model to find the best plan for the electrical distribution systems (EDSs) in a short-term planning horizon. In this regard, the energy delivered by the substation and the total investment cost are minimized while the stochasticity related with the demand and photovoltaic (PV) generation is modeled via external uncertainty indexes. Considering PV generation, switchable and fixed capacitor banks (CBs), voltage regulators (VRs), conductor replacement, as well as operating costs results in a mixed-integer nonlinear programming (MINLP) model. However, to obtain the globally optimal solution, this highly nonlinear model, using appropriate linearization techniques, is recast to an MILP model. In order to validate and show the effectiveness of the proposed model, a 42-node system is considered in detail.
publishDate 2017
dc.date.none.fl_str_mv 2017-07-12
2018-12-11T17:33:27Z
2018-12-11T17:33:27Z
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/EEEIC.2017.7977735
Conference Proceedings - 2017 17th IEEE International Conference on Environment and Electrical Engineering and 2017 1st IEEE Industrial and Commercial Power Systems Europe, EEEIC / I and CPS Europe 2017.
http://hdl.handle.net/11449/179075
10.1109/EEEIC.2017.7977735
2-s2.0-85026770512
url http://dx.doi.org/10.1109/EEEIC.2017.7977735
http://hdl.handle.net/11449/179075
identifier_str_mv Conference Proceedings - 2017 17th IEEE International Conference on Environment and Electrical Engineering and 2017 1st IEEE Industrial and Commercial Power Systems Europe, EEEIC / I and CPS Europe 2017.
10.1109/EEEIC.2017.7977735
2-s2.0-85026770512
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Conference Proceedings - 2017 17th IEEE International Conference on Environment and Electrical Engineering and 2017 1st IEEE Industrial and Commercial Power Systems Europe, EEEIC / I and CPS Europe 2017
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_ 1803047038546345984