Tratamento de incertezas no projeto de sistemas de distribuição de energia elétrica: uma abordagem nebulosa

Abstract

The present work aims for modeling the uncertainties in the power distribution system design. According to the literature, this kind of problem has been tackled more recently as follows: the optimization process uses a 'most likely' scenario for the load expansion and then a Multiobjective Sensibility Analysis is performed for several load scenarios using Monte Carlo Simulations in which the uncertainties are modelled by using some probability distribution. In this present work the uncertainties have been incorporated inside the optimization process by using fuzzy techniques. More flexible and robust solutions have been found. The genetic algorithm has been adapted for fuzzy optimization using known approaches and a new 'fitness attribution' has been implemented in the NSGA II program. The results obtained by the fuzzy optimization methodology are submitted to the Multiobjective Sensitivity Analysis and they are compared with the results found in the literature. The results gained here are very promising since they have shown a wider set of solutions for which the established feasibility rate is achieved.