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(Referência obtida automaticamente do Web of Science, por meio da informação sobre o financiamento pela FAPESP e o número do processo correspondente, incluída na publicação pelos autores.)

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

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Autor(es):
Pourakbari-Kasmaei, Mandi [1] ; Sanches Mantovani, Jose Roberto [1]
Número total de Autores: 2
Afiliação do(s) autor(es):
[1] State Univ Sao Paulo, Dept Elect Engn, Ilha Solteira - Brazil
Número total de Afiliações: 1
Tipo de documento: Artigo Científico
Fonte: INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS; v. 97, p. 240-249, APR 2018.
Citações Web of Science: 9
Resumo

There 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. (AU)

Processo FAPESP: 16/14319-7 - Alocação on-line de pegada de carbono (carbon footprint): um modelo integrado para gerenciar a redução de emissão de gases de efeito estufa e a demanda de energia elétrica
Beneficiário:Mahdi Pourakbari Kasmaei
Modalidade de apoio: Bolsas no Exterior - Estágio de Pesquisa - Pós-Doutorado
Processo FAPESP: 14/22828-3 - Desenvolvimentos de modelos de programação não linear inteira mista para solução de problema de fluxo de potência ótimo ativo e reativo para sistemas com geradores multi-combustíveis considerando restrições ambientais
Beneficiário:Mahdi Pourakbari Kasmaei
Modalidade de apoio: Bolsas no Brasil - Pós-Doutorado