Enhancing Stability of Hydel Power System Dynamics using Bio Inspired Genetic and PSO Algorithms

Abstract

With the increasing complexity of Modern Interconnected Power Systems, Low frequency inertial oscillations after a disturbance in a Power System are becoming one of the major problem. This paper provides a systematic approach to damp the Low frequency inertial oscillations observed in the Hydel Power System based on Bio inspired Genetic (GA) and Particle Swarm Optimization (PSO) algorithms. The design problem is formulated as a Multiobjective Optimization criterion comprising of Damping ratio based and Time domain based objective functions to compute the optimal controller parameters and also to minimize the integral squared error involving rotor speed and angle deviations for stability. The Contrasting feature of this work is the Mathematical modeling and Simulation of the Hydel power system dynamics model comprising of hydel governor, turbine and generator. To validate the effectiveness and robustness of the proposed controller, Non linear simulations has been implemented under various system loading conditions and also under various parameter variations of the model considered. Also a comparative study has been done between the Bio inspired based controllers and the conventional lead lag controller.