Specialized Genetic Algorithm of Chu-Beasley Applied to the Distribution System Reconfiguration Problem Considering Several Demand Scenarios

Bibliographic Details
Main Author: Souza, Simone S. F. [UNESP]
Publication Date: 2015
Other Authors: Romero, Ruben [UNESP], Pereira, Jorge, Saraiva, J. T., IEEE
Format: Conference object
Language: eng
Source: Repositório Institucional da UNESP
Download full: http://hdl.handle.net/11449/161771
Summary: This paper describes the application of the specialized genetic algorithm of Chu-Beasley to solve the Distribution System Reconfiguration, DSR, problem considering different demand scenarios. This algorithm is an approach inspired in the natural selection and evolution of species. The reconfiguration problem of distribution networks taking into account different demand scenarios aims at identifying the most adequate radial topology of a distribution system assuming that this topology is used for all demand scenarios under study. This search is driven by the minimization of the cost of energy losses in the network along a full operation year. The performance of the algorithm is evaluated considering test systems having 33, 70, 84 and 136 buses and a real system with 417 buses. The obtained results confirm the robustness and efficiency of the developed approach and its potential to be used in distribution control centers.
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spelling Specialized Genetic Algorithm of Chu-Beasley Applied to the Distribution System Reconfiguration Problem Considering Several Demand ScenariosDistribution System ReconfigurationDemand scenariosSpecialized Genetic Algorithm of Chu-BeasleyMixed-Integer Nonlinear Programming ProblemThis paper describes the application of the specialized genetic algorithm of Chu-Beasley to solve the Distribution System Reconfiguration, DSR, problem considering different demand scenarios. This algorithm is an approach inspired in the natural selection and evolution of species. The reconfiguration problem of distribution networks taking into account different demand scenarios aims at identifying the most adequate radial topology of a distribution system assuming that this topology is used for all demand scenarios under study. This search is driven by the minimization of the cost of energy losses in the network along a full operation year. The performance of the algorithm is evaluated considering test systems having 33, 70, 84 and 136 buses and a real system with 417 buses. The obtained results confirm the robustness and efficiency of the developed approach and its potential to be used in distribution control centers.UNESP Univ Estadual Paulista, Dept Elect Engn, Ilha Solteira, SP, BrazilUniv Porto, INESC TEC, Oporto, PortugalUniv Porto, Fac Econ, Oporto, PortugalUniv Porto, Fac Engn, Oporto, PortugalUNESP Univ Estadual Paulista, Dept Elect Engn, Ilha Solteira, SP, BrazilIeeeUniversidade Estadual Paulista (Unesp)Univ PortoSouza, Simone S. F. [UNESP]Romero, Ruben [UNESP]Pereira, JorgeSaraiva, J. T.IEEE2018-11-26T16:48:33Z2018-11-26T16:48:33Z2015-01-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/conferenceObject52015 Ieee Eindhoven Powertech. New York: Ieee, 5 p., 2015.http://hdl.handle.net/11449/161771WOS:000380546800065Web of Sciencereponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPeng2015 Ieee Eindhoven Powertechinfo:eu-repo/semantics/openAccess2024-07-04T19:11:50Zoai:repositorio.unesp.br:11449/161771Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestrepositoriounesp@unesp.bropendoar:29462024-07-04T19:11:50Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false
dc.title.none.fl_str_mv Specialized Genetic Algorithm of Chu-Beasley Applied to the Distribution System Reconfiguration Problem Considering Several Demand Scenarios
title Specialized Genetic Algorithm of Chu-Beasley Applied to the Distribution System Reconfiguration Problem Considering Several Demand Scenarios
spellingShingle Specialized Genetic Algorithm of Chu-Beasley Applied to the Distribution System Reconfiguration Problem Considering Several Demand Scenarios
Souza, Simone S. F. [UNESP]
Distribution System Reconfiguration
Demand scenarios
Specialized Genetic Algorithm of Chu-Beasley
Mixed-Integer Nonlinear Programming Problem
title_short Specialized Genetic Algorithm of Chu-Beasley Applied to the Distribution System Reconfiguration Problem Considering Several Demand Scenarios
title_full Specialized Genetic Algorithm of Chu-Beasley Applied to the Distribution System Reconfiguration Problem Considering Several Demand Scenarios
title_fullStr Specialized Genetic Algorithm of Chu-Beasley Applied to the Distribution System Reconfiguration Problem Considering Several Demand Scenarios
title_full_unstemmed Specialized Genetic Algorithm of Chu-Beasley Applied to the Distribution System Reconfiguration Problem Considering Several Demand Scenarios
title_sort Specialized Genetic Algorithm of Chu-Beasley Applied to the Distribution System Reconfiguration Problem Considering Several Demand Scenarios
author Souza, Simone S. F. [UNESP]
author_facet Souza, Simone S. F. [UNESP]
Romero, Ruben [UNESP]
Pereira, Jorge
Saraiva, J. T.
IEEE
author_role author
author2 Romero, Ruben [UNESP]
Pereira, Jorge
Saraiva, J. T.
IEEE
author2_role author
author
author
author
dc.contributor.none.fl_str_mv Universidade Estadual Paulista (Unesp)
Univ Porto
dc.contributor.author.fl_str_mv Souza, Simone S. F. [UNESP]
Romero, Ruben [UNESP]
Pereira, Jorge
Saraiva, J. T.
IEEE
dc.subject.por.fl_str_mv Distribution System Reconfiguration
Demand scenarios
Specialized Genetic Algorithm of Chu-Beasley
Mixed-Integer Nonlinear Programming Problem
topic Distribution System Reconfiguration
Demand scenarios
Specialized Genetic Algorithm of Chu-Beasley
Mixed-Integer Nonlinear Programming Problem
description This paper describes the application of the specialized genetic algorithm of Chu-Beasley to solve the Distribution System Reconfiguration, DSR, problem considering different demand scenarios. This algorithm is an approach inspired in the natural selection and evolution of species. The reconfiguration problem of distribution networks taking into account different demand scenarios aims at identifying the most adequate radial topology of a distribution system assuming that this topology is used for all demand scenarios under study. This search is driven by the minimization of the cost of energy losses in the network along a full operation year. The performance of the algorithm is evaluated considering test systems having 33, 70, 84 and 136 buses and a real system with 417 buses. The obtained results confirm the robustness and efficiency of the developed approach and its potential to be used in distribution control centers.
publishDate 2015
dc.date.none.fl_str_mv 2015-01-01
2018-11-26T16:48:33Z
2018-11-26T16:48:33Z
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 2015 Ieee Eindhoven Powertech. New York: Ieee, 5 p., 2015.
http://hdl.handle.net/11449/161771
WOS:000380546800065
identifier_str_mv 2015 Ieee Eindhoven Powertech. New York: Ieee, 5 p., 2015.
WOS:000380546800065
url http://hdl.handle.net/11449/161771
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 2015 Ieee Eindhoven Powertech
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eu_rights_str_mv openAccess
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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 repositoriounesp@unesp.br
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