Algoritmo Evolutivo Multiobjetivo Aplicado ao Problema de Luxo de Potência Ótimo
(Multi Objective Evolutionary Algorithm Applied to the Optimal Power Flow Problem)
Elizete de Andrade Amorim (email@example.com)1, Selma Helena Marchiori Hashimoto (firstname.lastname@example.org)1, Flávio Guilherme de Melo Lima (email@example.com)1, José Roberto Sanches Mantovani (firstname.lastname@example.org)2
1Universidade Federal de Mato Grosso do Sul2Universidade Estadual Paulista
This paper appears in: Revista IEEE América Latina
Publication Date: June 2010
Volume: 8, Issue: 3
This work presents the application of a multiobjective evolutionary algorithm (MOEA) for optimal power flow (OPF) solution. The OPF is modeled as a constrained nonlinear optimization problem, non-convex of large-scale, with continuous and discrete variables. The violated inequality constraints are treated as objective function of the problem. This strategy allows attending the physical and operational restrictions without compromise the quality of the found solutions. The developed MOEA is based on the theory of Pareto and employs a diversity-preserving mechanism to overcome the premature convergence of algorithm and local optimal solutions. Fuzzy set theory is employed to extract the best compromises of the Pareto set. Results for the IEEE-30,RTS-96 and IEEE-354 test systems are presents to validate the efficiency of proposed model and solution technique.
Multiobjective Evolutionary Algorithm, Optimal Power Flow, Multiobjective Optimization.
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