Genetic Algorithm based controllers for Robust Stability Enhancement of interconnected Power System with wind power penetration

This work presents genetic algorithm-based power system stabilizers for conventional generators and genetic algorithm-based PI controllers for double fed induction generators (DFIGs) for enhancing dynamic stability of inter connected power system. This methodology is to inspect the vigorous dependability examination of various power frameworks, for example, wind power penetrations and fault conditions. The approach enjoys a few benefits compared with our past work. In the this method the parameters of DFIG controllers and power system stabilizers are tuned using genetic algorithm by maximizing fitness function, this function is formulated as a reciprocal of integral time area error (ITAE) of speed deviations of generators. In this paper the controller is examined on a classical “4 generator 11-bus” assessed energy framework, performance is compared with new set approach (Km theory). Results demonstrated that the controller is effectively damping the oscillations compared with new set approach.