Logically constrained optimal power flow: Solver-based mixed-integer nonlinear programming model

Registro completo de metadados
MetadadosDescriçãoIdioma
Autor(es): dc.contributorUniversidade Estadual Paulista (UNESP)-
Autor(es): dc.creatorPourakbari-Kasmaei, Mandi-
Autor(es): dc.creatorSanches Mantovani, Jose Roberto-
Data de aceite: dc.date.accessioned2021-03-10T23:57:04Z-
Data de disponibilização: dc.date.available2021-03-10T23:57:04Z-
Data de envio: dc.date.issued2018-11-26-
Data de envio: dc.date.issued2018-11-26-
Data de envio: dc.date.issued2018-04-01-
Fonte completa do material: dc.identifierhttp://dx.doi.org/10.1016/j.ijepes.2017.11.010-
Fonte completa do material: dc.identifierhttp://hdl.handle.net/11449/163833-
Fonte: dc.identifier.urihttp://educapes.capes.gov.br/handle/11449/163833-
Descrição: dc.descriptionFundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)-
Descrição: dc.descriptionCoordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)-
Descrição: dc.descriptionConselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)-
Descrição: dc.descriptionProcesso FAPESP: 2014/22828-3-
Descrição: dc.descriptionProcesso FAPESP: 2016/14319-7-
Descrição: dc.descriptionCNPq: 305371/2012-6-
Descrição: dc.descriptionThere is increasing evidence of the shortage of solver-based models for solving logically-constrained AC optimal power flow problem (LCOPF). Although in the literature the heuristic-based models have been widely used to handle the LCOPF problems with logical terms such as conditional statements, logical-and, logical-or, etc., their requirement of several trials and adjustments plagues finding a trustworthy solution. On the other hand, a well-defined solver-based model is of much interest in practice, due to rapidity and precision in finding an optimal solution. To remedy this shortcoming, in this paper we provide a solver-friendly procedure to recast the logical constraints to solver-based mixed-integer nonlinear programming (MINLP) terms. We specifically investigate the recasting of logical constraints into the terms of the objective function, so it facilitates the pre-solving and probing techniques of commercial solvers and consequently results in a higher computational efficiency. By applying this recast method to the problem, two sub-power- and sub-function-based MINLP models, namely SP-MINLP and SF-MINLP, respectively, are proposed. Results not only show the superiority of the proposed models in finding a better optimal solution, compared to the existing approaches in the literature, but also the effectiveness and computational tractability in solving large-scale power systems under different configurations.-
Formato: dc.format240-249-
Idioma: dc.languageen-
Publicador: dc.publisherElsevier B.V.-
Relação: dc.relationInternational Journal Of Electrical Power & Energy Systems-
Relação: dc.relation1,276-
Direitos: dc.rightsopenAccess-
Palavras-chave: dc.subjectFACTS devices-
Palavras-chave: dc.subjectLogical constraint-
Palavras-chave: dc.subjectMixed-integer nonlinear programming-
Palavras-chave: dc.subjectOptimal power flow-
Palavras-chave: dc.subjectSolver-based model-
Palavras-chave: dc.subjectNon-smooth terms-
Título: dc.titleLogically constrained optimal power flow: Solver-based mixed-integer nonlinear programming model-
Tipo de arquivo: dc.typelivro digital-
Aparece nas coleções:Repositório Institucional - Unesp

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