An encoding technique for multiobjective evolutionary algorithms applied to power distribution system reconfiguration.
Network reconfiguration is an alternative to reduce power losses and optimize the operation of power distribution systems. In this paper, an encoding scheme for evolutionary algorithms is proposed in order to search efficiently for the Pareto-optimal solutions during the reconfiguration of power distribution systems considering multiobjective optimization. The encoding scheme is based on the edge window decoder (EWD) technique, which was embedded in the Strength Pareto Evolutionary Algorithm 2 (SPEA2) and the Nondominated Sorting Genetic Algorithm II (NSGA-II). The effectiveness of the encoding scheme was proved by solving a test problem for which the true Pareto-optimal solutions are known in advance. In order to prove the practicability of the encoding scheme, a real distribution system was used to find the near Pareto-optimal solutions for different objective functions to optimize.
Instituto Tecnológico de Morelia, Avenida Tecnológico 1500, 58120 Morelia, MICH, Mexico.
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JL
Guardado
Instituto Tecnológico de Morelia, Avenida Tecnológico 1500, 58120 Morelia, MICH, Mexico.
F
F
Rivas-Davalos
Instituto Tecnológico Superior de Irapuato, Carretera Irapuato, Silao Km. 12.5, 36821 Irapuato, GTO, Mexico.
J
J
Torres
Instituto Tecnológico de Morelia, Avenida Tecnológico 1500, 58120 Morelia, MICH, Mexico.
S
S
Maximov
Instituto Tecnológico de Morelia, Avenida Tecnológico 1500, 58120 Morelia, MICH, Mexico.
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E
Melgoza
D000465:Algorithms; D005075:Biological Evolution; D015233:Models, Statistical