Enhanced control of electrical power system oscillations by GA optimized damping controller

Abstract

A genetic algorithm based optimization technique for optimum design of power system damping controller in a multi-machine power system has been developed. In this technique, the genetic algorithm involves an objective function that is based on the integral of squared-time- squared-error criterion. Parameters of the power system stabilizers are tuned via simulation experiments based on a non-linear model of the system. The dynamic performance has been investigated under both small and large disturbance perturbation, and compared with the case of conventional optimization using phase compensation. Simulation experiments have demonstrated the proposed genetic-algorithm optimized power system stabilizers do enhance quality dynamic performance over a wide range of operating conditions by effectively damping both local and inter-area oscillation modes.