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

Abstract

This work proposes 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 approach is developed to examine the robust stability analysis of power systems, such as
power systems with wind power penetrations and fault conditions. The proposed approach has several advantages
compared with our previous work. In the proposed 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. Proposed controller is tested on a classical 4-
generator 11-bus test power system, performance is compared with new set approach (Km theory). Results demonstrated
that the proposed controller is effectively damping the oscillations compared with new set approach.