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The Scientific World Journal
Volume 2014, Article ID 506769, 9 pages
http://dx.doi.org/10.1155/2014/506769
Research Article

An Encoding Technique for Multiobjective Evolutionary Algorithms Applied to Power Distribution System Reconfiguration

1Instituto Tecnológico de Morelia, Avenida Tecnológico 1500, 58120 Morelia, MICH, Mexico
2Instituto Tecnológico Superior de Irapuato, Carretera Irapuato, Silao Km. 12.5, 36821 Irapuato, GTO, Mexico

Received 7 May 2014; Accepted 3 September 2014; Published 23 October 2014

Academic Editor: Manoj Jha

Copyright © 2014 J. L. Guardado et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

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.