Robust Design of Power Distribution Systems Using an Enhanced Multi-Objective Genetic Algorithm

Cristiane G. Taroco, Eduardo G. Carrano and Oriane M. Neto
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Cristiane G. Taroco: Universidade Federal de Minas Gerais, Brazil
Eduardo G. Carrano: Centro Federal de Educação Tecnológica de Minas Gerais, Brazil
Oriane M. Neto: Universidade Federal de Minas Gerais, Brazil

International Journal of Natural Computing Research (IJNCR), 2010, vol. 1, issue 2, 92-112

Abstract: The growing importance of electric distribution systems justifies new investments in their expansion and evolution. It is well known in the literature that optimization techniques can provide better allocation of the financial resources available for such a task, reducing total installation costs and power losses. In this work, the NSGA-II algorithm is used for obtaining a set of efficient solutions with regard to three objective functions, that is cost, reliability, and robustness. Initially, a most likely load scenario is considered for simulation. Next, the performances of the solutions achieved by the NSGA-II are evaluated under different load scenarios, which are generated by means of Monte Carlo Simulations. A Multiobjective Sensitivity Analysis is performed for selecting the most robust solutions. Finally, those solutions are submitted to a local search algorithm to estimate a Pareto set composed of just robust solutions only.

Date: 2010
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Persistent link: https://EconPapers.repec.org/RePEc:igg:jncr00:v:1:y:2010:i:2:p:92-112

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