Multistage reliability-based expansion planning of AC distribution networks using a mixed-integer linear programming model
Autor(a) principal: | |
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Data de Publicação: | 2022 |
Outros Autores: | , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UNESP |
Texto Completo: | http://dx.doi.org/10.1016/j.ijepes.2021.107916 http://hdl.handle.net/11449/223297 |
Resumo: | A new mathematical model for the multistage distribution network expansion planning problem considering reliability is proposed in this paper. Decisions related to substation and branch expansion are driven by the minimization of the total cost, which comprises investment and operating costs including the impact of reliability. The proposed model features two main novelties. First, a set of novel algebraic expressions is devised for a standard reliability index, namely the expected energy not supplied. As a result, the dependence of reliability on network topology is explicitly and effectively cast in the mathematical formulation of the planning problem at hand. In addition, the effect of the network is characterized by a computationally efficient piecewise linear representation of the ac power flow model that takes into account both real and reactive power. The resulting optimization problem is formulated as an instance of mixed-integer linear programming, which provides a suitable framework for the attainment of high-quality solutions with acceptable computational effort using efficient off-the-shelf software with well-known convergence properties. The effectiveness of the proposed planning methodology is empirically demonstrated by providing cheaper expansion plans that enhance system reliability and by achieving better computational results as compared with state-of-the-art models. |
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Multistage reliability-based expansion planning of AC distribution networks using a mixed-integer linear programming modelAC network modelDistribution network expansion planningMixed-integer linear programmingMultistageReliabilityA new mathematical model for the multistage distribution network expansion planning problem considering reliability is proposed in this paper. Decisions related to substation and branch expansion are driven by the minimization of the total cost, which comprises investment and operating costs including the impact of reliability. The proposed model features two main novelties. First, a set of novel algebraic expressions is devised for a standard reliability index, namely the expected energy not supplied. As a result, the dependence of reliability on network topology is explicitly and effectively cast in the mathematical formulation of the planning problem at hand. In addition, the effect of the network is characterized by a computationally efficient piecewise linear representation of the ac power flow model that takes into account both real and reactive power. The resulting optimization problem is formulated as an instance of mixed-integer linear programming, which provides a suitable framework for the attainment of high-quality solutions with acceptable computational effort using efficient off-the-shelf software with well-known convergence properties. The effectiveness of the proposed planning methodology is empirically demonstrated by providing cheaper expansion plans that enhance system reliability and by achieving better computational results as compared with state-of-the-art models.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)Ministerio de Ciencia, Innovación y UniversidadesDepartment of Electrical Engineering São Paulo State UniversityEscuela Técnica Superior de Ingeniería Industrial Universidad de Castilla-La ManchaSchool of Energy Engineering São Paulo State UniversityDepartment of Electrical Engineering São Paulo State UniversitySchool of Energy Engineering São Paulo State UniversityCNPq: 152002/2016-2FAPESP: 2017/02831-8FAPESP: 2018/ 20990–9CNPq: 313047/2017-0Ministerio de Ciencia, Innovación y Universidades: RTI2018-096108-A-I00Ministerio de Ciencia, Innovación y Universidades: RTI2018-098703-B-I00Universidade Estadual Paulista (UNESP)Universidad de Castilla-La ManchaTabares, Alejandra [UNESP]Muñoz-Delgado, GregorioFranco, John F. [UNESP]Arroyo, José M.Contreras, Javier2022-04-28T19:49:45Z2022-04-28T19:49:45Z2022-06-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlehttp://dx.doi.org/10.1016/j.ijepes.2021.107916International Journal of Electrical Power and Energy Systems, v. 138.0142-0615http://hdl.handle.net/11449/22329710.1016/j.ijepes.2021.1079162-s2.0-85123199492Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengInternational Journal of Electrical Power and Energy Systemsinfo:eu-repo/semantics/openAccess2022-04-28T19:49:45Zoai:repositorio.unesp.br:11449/223297Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T17:08:12.446414Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false |
dc.title.none.fl_str_mv |
Multistage reliability-based expansion planning of AC distribution networks using a mixed-integer linear programming model |
title |
Multistage reliability-based expansion planning of AC distribution networks using a mixed-integer linear programming model |
spellingShingle |
Multistage reliability-based expansion planning of AC distribution networks using a mixed-integer linear programming model Tabares, Alejandra [UNESP] AC network model Distribution network expansion planning Mixed-integer linear programming Multistage Reliability |
title_short |
Multistage reliability-based expansion planning of AC distribution networks using a mixed-integer linear programming model |
title_full |
Multistage reliability-based expansion planning of AC distribution networks using a mixed-integer linear programming model |
title_fullStr |
Multistage reliability-based expansion planning of AC distribution networks using a mixed-integer linear programming model |
title_full_unstemmed |
Multistage reliability-based expansion planning of AC distribution networks using a mixed-integer linear programming model |
title_sort |
Multistage reliability-based expansion planning of AC distribution networks using a mixed-integer linear programming model |
author |
Tabares, Alejandra [UNESP] |
author_facet |
Tabares, Alejandra [UNESP] Muñoz-Delgado, Gregorio Franco, John F. [UNESP] Arroyo, José M. Contreras, Javier |
author_role |
author |
author2 |
Muñoz-Delgado, Gregorio Franco, John F. [UNESP] Arroyo, José M. Contreras, Javier |
author2_role |
author author author author |
dc.contributor.none.fl_str_mv |
Universidade Estadual Paulista (UNESP) Universidad de Castilla-La Mancha |
dc.contributor.author.fl_str_mv |
Tabares, Alejandra [UNESP] Muñoz-Delgado, Gregorio Franco, John F. [UNESP] Arroyo, José M. Contreras, Javier |
dc.subject.por.fl_str_mv |
AC network model Distribution network expansion planning Mixed-integer linear programming Multistage Reliability |
topic |
AC network model Distribution network expansion planning Mixed-integer linear programming Multistage Reliability |
description |
A new mathematical model for the multistage distribution network expansion planning problem considering reliability is proposed in this paper. Decisions related to substation and branch expansion are driven by the minimization of the total cost, which comprises investment and operating costs including the impact of reliability. The proposed model features two main novelties. First, a set of novel algebraic expressions is devised for a standard reliability index, namely the expected energy not supplied. As a result, the dependence of reliability on network topology is explicitly and effectively cast in the mathematical formulation of the planning problem at hand. In addition, the effect of the network is characterized by a computationally efficient piecewise linear representation of the ac power flow model that takes into account both real and reactive power. The resulting optimization problem is formulated as an instance of mixed-integer linear programming, which provides a suitable framework for the attainment of high-quality solutions with acceptable computational effort using efficient off-the-shelf software with well-known convergence properties. The effectiveness of the proposed planning methodology is empirically demonstrated by providing cheaper expansion plans that enhance system reliability and by achieving better computational results as compared with state-of-the-art models. |
publishDate |
2022 |
dc.date.none.fl_str_mv |
2022-04-28T19:49:45Z 2022-04-28T19:49:45Z 2022-06-01 |
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/10.1016/j.ijepes.2021.107916 International Journal of Electrical Power and Energy Systems, v. 138. 0142-0615 http://hdl.handle.net/11449/223297 10.1016/j.ijepes.2021.107916 2-s2.0-85123199492 |
url |
http://dx.doi.org/10.1016/j.ijepes.2021.107916 http://hdl.handle.net/11449/223297 |
identifier_str_mv |
International Journal of Electrical Power and Energy Systems, v. 138. 0142-0615 10.1016/j.ijepes.2021.107916 2-s2.0-85123199492 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
International Journal of Electrical Power and Energy Systems |
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_ |
1808128759890444288 |