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Journal of Electrical and Computer Engineering
Volume 2012, Article ID 738409, 5 pages
Research Article

Evolutionary Optimization of Electric Power Distribution Using the Dandelion Code

1Departamento de Ingeniería Eléctrica, Universidad de Santiago de Chile, Avenida Ecuador 3659, Santiago, Chile
2Departamento de Ingeniería Informática, Universidad de Santiago de Chile, Avenida Ecuador 3659, Santiago, Chile

Received 16 August 2011; Revised 12 November 2011; Accepted 12 November 2011

Academic Editor: Edgar Carreno

Copyright © 2012 Jorge Sabattin 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.


Planning primary electric power distribution involves solving an optimization problem using nonlinear components, which makes it difficult to obtain the optimum solution when the problem has dimensions that are found in reality, in terms of both the installation cost and the power loss cost. To tackle this problem, heuristic methods have been used, but even when sacrificing quality, finding the optimum solution still represents a computational challenge. In this paper, we study this problem using genetic algorithms. With the help of a coding scheme based on the dandelion code, these genetic algorithms allow larger instances of the problem to be solved. With the stated approach, we have solved instances of up to 40,000 consumer nodes when considering 20 substations; the total cost deviates 3.1% with respect to a lower bound that considers only the construction costs of the network.