Genetic algorithm-based optimum performance of compensated self-excited induction generator

The self-excited induction generator (SEIG) shows drooping voltage with the load and thus exhibits poor performance, which can be improved through short-shunt SEIG. In this paper, the series and shunt capacitances for short-shunt SEIG are selected to provide optimum voltage regulation and to provide optimum performance, a combination of voltage regulation and loadability. Correspondingly, the optimization is attempted using genetic algorithm (GA). The GA, a global search and optimization method, provides optimum values of capacitances. The study is carried out for resistive and inductive loads and the results are validated experimentally