Fuzzy Rule Table Optimization Of Power System Stabilizer Using Genetic Algorithm

Abstract

This paper investigated the rule table optimization of fuzzy power system stabilizer (FPSS) benefiting from rule basis of related previous studies. In the previous studies, fuzzy rules for Power System Stabilizer (PSS) were obtained by trial and error according to the experience of experts. There were a few rule tables occurred in that way in the literature. In this subject field, five rule tables with a few differences among them were taken. Genetic algorithm (GA) was employed as an optimization method, and single machine infinite bus (SMIB) model was used for simulation system. This work proposed to contribute optimization performance of FPSS adding these rule tables to the initial population of GA. Thus GAs reached an optimum solution more quickly. Simulation studies and the integral of absolute error (IAE) performance results for four loading conditions were shown. The effectiveness of the proposed approach was discussed by comparing it with the five rule tables.