POWER SYSTEM PLANNING AND OPERATION

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dc.contributor.authorSimon, Sishaj Pulikottil
dc.contributor.authorPadhy, Narayana Prasad
dc.contributor.authorPark, Jong-Bae
dc.contributor.authorLee, Kwang Y.
dc.contributor.authorZhou, Ming
dc.contributor.authorXia, Shu
dc.contributor.authorda Silva, Anna Carolina R.H.
dc.contributor.authorChoi, Jaeseok
dc.contributor.authorLee, Yeonchan
dc.contributor.authorLambert-Torres, Germano
dc.contributor.authorSalomon, Camila Paes
dc.contributor.authorda Silva, Luiz Eduardo Borges
dc.contributor.authorBai, Wenlei
dc.contributor.authorEke, Ibrahim
dc.contributor.authorRueda, Jose
dc.contributor.authorCarvalho, Leonel
dc.contributor.authorMiranda, Vladimiro
dc.contributor.authorErlich, Istvan
dc.contributor.authorTheologi, Aimilia-Myrsini
dc.contributor.authorAsada, Eduardo N.
dc.contributor.authorSouza, Aldir S.
dc.contributor.authorRomero, Rubén [UNESP]
dc.contributor.institutionNational Institute of Technology Tiruchirappalli
dc.contributor.institutionIndian Institute of Technology Roorkee
dc.contributor.institutionKonkuk University
dc.contributor.institutionBaylor University
dc.contributor.institutionNorth China Electric Power University
dc.contributor.institutionEletrobras
dc.contributor.institutionGyeongsang National University
dc.contributor.institutionGnarus Institute
dc.contributor.institutionItajuba Federal University
dc.contributor.institutionABB Enterprises Software Inc.
dc.contributor.institutionKirikkale University
dc.contributor.institutionTU Delft
dc.contributor.institutionINESC TEC
dc.contributor.institutionUniversity of Porto
dc.contributor.institutionUniversity of Duisburg-Essen
dc.contributor.institutionJedlix Smart Charging
dc.contributor.institutionUniversidade de São Paulo (USP)
dc.contributor.institutionState University of Piauí
dc.contributor.institutionUniversidade Estadual Paulista (UNESP)
dc.date.accessioned2023-03-02T09:48:57Z
dc.date.available2023-03-02T09:48:57Z
dc.date.issued2020-01-01
dc.description.abstractThis chapter provides implementation of various optimization algorithms to various power system problems that utilize power flow calculations. Determination of the schedule (ON/OFF status and amount of power generated) of generating units within a power system results in great saving for electric utilities. The unit commitment problem can be formulated in order to minimize the total operating cost, satisfying the system, the unit, and several operational constraints. The power transfer limit of overhead transmission lines (OTLs) is an important constraint for power systems’ planning and operation. This constraint plays an essential role in the secure and economic management of power systems. The chapter presents economic dispatch problem by considering GAs and particle swarm optimization (PSO) in complex power system analysis. It uses a hybrid PSO to solve load flow problem while uses artificial bee colony optimization for solving the optimal power flow problem.en
dc.description.affiliationNational Institute of Technology Tiruchirappalli, Tamilnadu
dc.description.affiliationIndian Institute of Technology Roorkee, Uttarakhand
dc.description.affiliationKonkuk University
dc.description.affiliationBaylor University
dc.description.affiliationNorth China Electric Power University
dc.description.affiliationEletrobras
dc.description.affiliationGyeongsang National University
dc.description.affiliationGnarus Institute, MG
dc.description.affiliationItajuba Federal University, MG
dc.description.affiliationABB Enterprises Software Inc.
dc.description.affiliationKirikkale University
dc.description.affiliationTU Delft
dc.description.affiliationINESC TEC
dc.description.affiliationINESC TEC University of Porto
dc.description.affiliationUniversity of Duisburg-Essen
dc.description.affiliationJedlix Smart Charging
dc.description.affiliationUniversity of São Paulo
dc.description.affiliationState University of Piauí, Piauí
dc.description.affiliationSão Paulo State University, São Paulo
dc.description.affiliationUnespSão Paulo State University, São Paulo
dc.format.extent39-225
dc.identifierhttp://dx.doi.org/10.1002/9781119602286.ch3
dc.identifier.citationApplications of Modern Heuristic Optimization Methods in Power and Energy Systems, p. 39-225.
dc.identifier.doi10.1002/9781119602286.ch3
dc.identifier.scopus2-s2.0-85135659431
dc.identifier.urihttp://hdl.handle.net/11449/242130
dc.language.isoeng
dc.relation.ispartofApplications of Modern Heuristic Optimization Methods in Power and Energy Systems
dc.sourceScopus
dc.subjectArtificial bee colony optimization
dc.subjectClassical constructive heuristic algorithms
dc.subjectOptimal power flow problem
dc.subjectParticle swarm optimization
dc.subjectPower system planning
dc.subjectUnit commitment problem
dc.titlePOWER SYSTEM PLANNING AND OPERATIONen
dc.typeCapítulo de livro
unesp.departmentEngenharia Elétrica - FEISpt

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Ilha Solteira - FEIS - Faculdade de Engenharia