Logotipo do repositório
 

Publicação:
Artificial immune networks Copt-aiNet and Opt-aiNet applied to the reconfiguration problem of radial electrical distribution systems

dc.contributor.authorSouza, Simone S. F. [UNESP]
dc.contributor.authorRomero, Ruben [UNESP]
dc.contributor.authorFranco, John F. [UNESP]
dc.contributor.institutionUniversidade Estadual Paulista (Unesp)
dc.date.accessioned2015-10-22T07:24:50Z
dc.date.available2015-10-22T07:24:50Z
dc.date.issued2015-02-01
dc.description.abstractThis paper presents two new approaches to solving the reconfiguration problem of electrical distribution systems (EDS) using the Copt-aiNet (Artificial Immune Network for Combinatorial Optimization) and Opt-aiNet (Artificial Immune Network for Optimization) algorithms. The Copt-aiNet and Opt-aiNet algorithms are efficient optimization techniques inspired by the immune network theory (aiNet). The reconfiguration problem is a complex combinatorial problem that aims at identifying the best radial topology for the EDS in order to minimize power losses. A specialized forward/backward radial power flow was used to evaluate each proposed solution proposal in order to determine its power losses and its feasibility regarding the operational constraints of the EDS. The algorithms were developed in the C++ programming language and test systems of 33, 70, 84, 119, and 136 nodes, along with a real system of 417 nodes, were used to validate the proposed method. The obtained results were compared with the best solutions found in the specialized literature in order to verify the efficiency of the proposed algorithms. (C) 2014 Elsevier B.V. All rights reserved.en
dc.description.affiliationFaculty of Engineering of Ilha Solteira, São Paulo State University, Ilha Solteira, SP, Brazil
dc.description.affiliationUnespFaculty of Engineering of Ilha Solteira, São Paulo State University, Ilha Solteira, SP, Brazil
dc.description.sponsorshipCoordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
dc.description.sponsorshipConselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
dc.description.sponsorshipFundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
dc.description.sponsorshipIdCAPES: BEX 3660/14-1
dc.description.sponsorshipIdFAPESP: 2012/01100-6
dc.format.extent304-312
dc.identifierhttp://www.sciencedirect.com/science/article/pii/S0378779614003666
dc.identifier.citationElectric Power Systems Research. Lausanne: Elsevier Science Sa, v. 119, p. 304-312, 2015.
dc.identifier.doi10.1016/j.epsr.2014.10.012
dc.identifier.issn0378-7796
dc.identifier.urihttp://hdl.handle.net/11449/129870
dc.identifier.wosWOS:000347756700033
dc.language.isoeng
dc.publisherElsevier B.V.
dc.relation.ispartofElectric Power Systems Research
dc.relation.ispartofjcr2.856
dc.relation.ispartofsjr1,048
dc.rights.accessRightsAcesso restrito
dc.sourceWeb of Science
dc.subjectArtificial immune networksen
dc.subjectCopt-aiNeten
dc.subjectMetaheuristicsen
dc.subjectOpt-aiNeten
dc.subjectReconfiguration of electrical distribution systemsen
dc.subjectReduction of power lossesen
dc.titleArtificial immune networks Copt-aiNet and Opt-aiNet applied to the reconfiguration problem of radial electrical distribution systemsen
dc.typeArtigo
dcterms.licensehttp://www.elsevier.com/about/open-access/open-access-policies/article-posting-policy
dcterms.rightsHolderElsevier B.V.
dspace.entity.typePublication
unesp.campusUniversidade Estadual Paulista (UNESP), Faculdade de Engenharia, Ilha Solteirapt
unesp.departmentEngenharia Elétrica - FEISpt

Arquivos