NSGA and SPEA applied to multiobjective design of power distribution systems

This paper presents, for the first time, an application of two well-know multiobjective optimization techniques, namely, nondominated sorting genetic algorithm (NSGA) and strength Pareto evolutionary algorithm (SPEA), to the multiobjective design of power distribution systems. These algorithms have been applied to a multiobjective optimization problem with some technical constraints, minimizing the total costs while maximizing the reliability of the power distribution system. The NSGA uses a fitness sharing scheme to achieve diversity among the obtained solutions. In SPEA, it is necessary to apply a reduction procedure because of the number of solutions. For this purpose, a fuzzy c-means (FCM) clustering algorithm has been applied, with this being the first time that an FCM algorithm in the SPEA has been used. The obtained results from both techniques have been compared, concluding that both offer similar efficiency in order to solve the stated multiobjective optimization problem. The developed methodology is applicable to practical cases of design, allowing for additional requirements that the designer imposes.