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High-performance hybrid genetic algorithm to solve transmission network expansion planning

dc.contributor.authorGallego, Luis A.
dc.contributor.authorGarces, Lina P.
dc.contributor.authorRahmani, Mohsen
dc.contributor.authorRomero, Ruben A. [UNESP]
dc.contributor.institutionUniversidade Estadual de Londrina (UEL)
dc.contributor.institutionUniversidade Federal de Goiás (UFG)
dc.contributor.institutionCarnegie Mellon Univ
dc.contributor.institutionUniversidade Estadual Paulista (Unesp)
dc.date.accessioned2018-11-26T17:31:19Z
dc.date.available2018-11-26T17:31:19Z
dc.date.issued2017-03-30
dc.description.abstractIn this study, a high-performance hybrid genetic algorithm (HGA) is proposed to solve static and multistage transmission network expansion planning (TNEP) problem. The main features of the HGA are: (i) it avoids homogenised solutions by using a special genetic algorithm as the backbone of the procedure, (ii) uses a powerful path-relinking algorithm for the deep exploration of local solutions, (iii) employs an efficient constructive heuristic algorithm for finding high-quality initial solutions and for improving solution qualities and (iv) uses a fast relaxation strategy for solving the linear programming problems required for calculating the fitness functions. This procedure will result in an intelligent exploration of a large search space in less amount of time. The proposed methodology is tested with three electrical systems: South Brazilian 46-bus, Colombian 93-bus and the North-Northeast Brazilian 87-bus.en
dc.description.affiliationUniv Estadual Londrina, Dept Elect Engn, Londrina, Brazil
dc.description.affiliationUniv Fed Goias, Elect Mech & Comp Engn Sch, Goiania, Go, Brazil
dc.description.affiliationCarnegie Mellon Univ, Engn & Publ Policy Dept, Pittsburgh, PA 15213 USA
dc.description.affiliationUniv Estadual Paulista, Dept Elect Engn, Ilha Solteira, Brazil
dc.description.affiliationUnespUniv Estadual Paulista, Dept Elect Engn, Ilha Solteira, Brazil
dc.format.extent1111-1118
dc.identifierhttp://dx.doi.org/10.1049/iet-gtd.2016.0511
dc.identifier.citationIet Generation Transmission & Distribution. Hertford: Inst Engineering Technology-iet, v. 11, n. 5, p. 1111-1118, 2017.
dc.identifier.doi10.1049/iet-gtd.2016.0511
dc.identifier.issn1751-8687
dc.identifier.urihttp://hdl.handle.net/11449/162776
dc.identifier.wosWOS:000400850600004
dc.language.isoeng
dc.publisherInst Engineering Technology-iet
dc.relation.ispartofIet Generation Transmission & Distribution
dc.relation.ispartofsjr0,907
dc.rights.accessRightsAcesso aberto
dc.sourceWeb of Science
dc.subjectpower transmission planning
dc.subjectgenetic algorithms
dc.subjectlinear programming
dc.subjecthigh-performance hybrid genetic algorithm
dc.subjecttransmission network expansion planning
dc.subjectstatic transmission network expansion planning problem
dc.subjectmultistage TNEP problem
dc.subjecthigh-performance HGA
dc.subjectpath-relinking algorithm
dc.subjectconstructive heuristic algorithm
dc.subjectfast relaxation strategy
dc.subjectlinear programming problem
dc.subjectfitness function
dc.subjectSouth Brazilian 46-bus electrical system
dc.subjectColombian 93-bus electrical system
dc.subjectNorth-Northeast Brazilian 87-bus electrical system
dc.titleHigh-performance hybrid genetic algorithm to solve transmission network expansion planningen
dc.typeArtigo
dcterms.rightsHolderInst Engineering Technology-iet
dspace.entity.typePublication
unesp.departmentEngenharia Elétrica - FEISpt

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