A modified Branch and Bound algorithm to solve the transmission expansion planning problem

Detalhes bibliográficos
Autor(a) principal: Delgado, M. A.J. [UNESP]
Data de Publicação: 2013
Outros Autores: Pourakbari-Kasmaei, M. [UNESP], Rider, M. J. [UNESP]
Tipo de documento: Artigo de conferência
Idioma: eng
Título da fonte: Repositório Institucional da UNESP
Texto Completo: http://dx.doi.org/10.1109/EEEIC-2.2013.6737914
http://hdl.handle.net/11449/227660
Resumo: In this paper a novel Branch and Bound (B&B) algorithm to solve the transmission expansion planning which is a non-convex mixed integer nonlinear programming problem (MINLP) is presented. Based on defining the options of the separating variables and makes a search in breadth, we call this algorithm a B&BML algorithm. The proposed algorithm is implemented in AMPL and an open source Ipopt solver is used to solve the nonlinear programming (NLP) problems of all candidates in the B&B tree. Strategies have been developed to address the problem of non-linearity and non-convexity of the search region. The proposed algorithm is applied to the problem of long-term transmission expansion planning modeled as an MINLP problem. The proposed algorithm has carried out on five commonly used test systems such as Garver 6-Bus, IEEE 24-Bus, 46-Bus South Brazilian test systems, Bolivian 57-Bus, and Colombian 93-Bus. Results show that the proposed methodology not only can find the best known solution but it also yields a large reduction between 24% to 77.6% in the number of NLP problems regarding to the size of the systems. © 2013 IEEE.
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spelling A modified Branch and Bound algorithm to solve the transmission expansion planning problemBranch and Bound algorithmNonlinear mixed integer programmingTransmission expansion planningIn this paper a novel Branch and Bound (B&B) algorithm to solve the transmission expansion planning which is a non-convex mixed integer nonlinear programming problem (MINLP) is presented. Based on defining the options of the separating variables and makes a search in breadth, we call this algorithm a B&BML algorithm. The proposed algorithm is implemented in AMPL and an open source Ipopt solver is used to solve the nonlinear programming (NLP) problems of all candidates in the B&B tree. Strategies have been developed to address the problem of non-linearity and non-convexity of the search region. The proposed algorithm is applied to the problem of long-term transmission expansion planning modeled as an MINLP problem. The proposed algorithm has carried out on five commonly used test systems such as Garver 6-Bus, IEEE 24-Bus, 46-Bus South Brazilian test systems, Bolivian 57-Bus, and Colombian 93-Bus. Results show that the proposed methodology not only can find the best known solution but it also yields a large reduction between 24% to 77.6% in the number of NLP problems regarding to the size of the systems. © 2013 IEEE.Department of Electrical and Electronic Engineering UNESP, Ilha SolteiraDepartment of Electrical and Electronic Engineering UNESP, Ilha SolteiraUniversidade Estadual Paulista (UNESP)Delgado, M. A.J. [UNESP]Pourakbari-Kasmaei, M. [UNESP]Rider, M. J. [UNESP]2022-04-29T07:14:25Z2022-04-29T07:14:25Z2013-12-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/conferenceObject234-238http://dx.doi.org/10.1109/EEEIC-2.2013.67379142013 13th International Conference on Environment and Electrical Engineering, EEEIC 2013 - Conference Proceedings, p. 234-238.http://hdl.handle.net/11449/22766010.1109/EEEIC-2.2013.67379142-s2.0-84897714613Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPeng2013 13th International Conference on Environment and Electrical Engineering, EEEIC 2013 - Conference Proceedingsinfo:eu-repo/semantics/openAccess2022-04-29T07:14:25Zoai:repositorio.unesp.br:11449/227660Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462022-04-29T07:14:25Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false
dc.title.none.fl_str_mv A modified Branch and Bound algorithm to solve the transmission expansion planning problem
title A modified Branch and Bound algorithm to solve the transmission expansion planning problem
spellingShingle A modified Branch and Bound algorithm to solve the transmission expansion planning problem
Delgado, M. A.J. [UNESP]
Branch and Bound algorithm
Nonlinear mixed integer programming
Transmission expansion planning
title_short A modified Branch and Bound algorithm to solve the transmission expansion planning problem
title_full A modified Branch and Bound algorithm to solve the transmission expansion planning problem
title_fullStr A modified Branch and Bound algorithm to solve the transmission expansion planning problem
title_full_unstemmed A modified Branch and Bound algorithm to solve the transmission expansion planning problem
title_sort A modified Branch and Bound algorithm to solve the transmission expansion planning problem
author Delgado, M. A.J. [UNESP]
author_facet Delgado, M. A.J. [UNESP]
Pourakbari-Kasmaei, M. [UNESP]
Rider, M. J. [UNESP]
author_role author
author2 Pourakbari-Kasmaei, M. [UNESP]
Rider, M. J. [UNESP]
author2_role author
author
dc.contributor.none.fl_str_mv Universidade Estadual Paulista (UNESP)
dc.contributor.author.fl_str_mv Delgado, M. A.J. [UNESP]
Pourakbari-Kasmaei, M. [UNESP]
Rider, M. J. [UNESP]
dc.subject.por.fl_str_mv Branch and Bound algorithm
Nonlinear mixed integer programming
Transmission expansion planning
topic Branch and Bound algorithm
Nonlinear mixed integer programming
Transmission expansion planning
description In this paper a novel Branch and Bound (B&B) algorithm to solve the transmission expansion planning which is a non-convex mixed integer nonlinear programming problem (MINLP) is presented. Based on defining the options of the separating variables and makes a search in breadth, we call this algorithm a B&BML algorithm. The proposed algorithm is implemented in AMPL and an open source Ipopt solver is used to solve the nonlinear programming (NLP) problems of all candidates in the B&B tree. Strategies have been developed to address the problem of non-linearity and non-convexity of the search region. The proposed algorithm is applied to the problem of long-term transmission expansion planning modeled as an MINLP problem. The proposed algorithm has carried out on five commonly used test systems such as Garver 6-Bus, IEEE 24-Bus, 46-Bus South Brazilian test systems, Bolivian 57-Bus, and Colombian 93-Bus. Results show that the proposed methodology not only can find the best known solution but it also yields a large reduction between 24% to 77.6% in the number of NLP problems regarding to the size of the systems. © 2013 IEEE.
publishDate 2013
dc.date.none.fl_str_mv 2013-12-01
2022-04-29T07:14:25Z
2022-04-29T07:14:25Z
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-2.2013.6737914
2013 13th International Conference on Environment and Electrical Engineering, EEEIC 2013 - Conference Proceedings, p. 234-238.
http://hdl.handle.net/11449/227660
10.1109/EEEIC-2.2013.6737914
2-s2.0-84897714613
url http://dx.doi.org/10.1109/EEEIC-2.2013.6737914
http://hdl.handle.net/11449/227660
identifier_str_mv 2013 13th International Conference on Environment and Electrical Engineering, EEEIC 2013 - Conference Proceedings, p. 234-238.
10.1109/EEEIC-2.2013.6737914
2-s2.0-84897714613
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 2013 13th International Conference on Environment and Electrical Engineering, EEEIC 2013 - Conference Proceedings
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv 234-238
dc.source.none.fl_str_mv Scopus
reponame:Repositório Institucional da UNESP
instname:Universidade Estadual Paulista (UNESP)
instacron:UNESP
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reponame_str Repositório Institucional da UNESP
collection Repositório Institucional da UNESP
repository.name.fl_str_mv Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)
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