Optimal Tuning of PSS Using Modified Hybrid Genetic Algorithm and PSO

This study proposed algorithm to tune and coordinate power system stabilizers (PSS) in multi-machine power systems. For a multi-machine power system, the coordination of the PSS parameters is generally formulated as an objective function with constraints including the damping ratio and damping factor. the parameters of proposed controller are optimized offline automatically by hybrid Genetic algorithm (GA) and Particle swarm optimization (PSO) techniques. In the proposed method, for achieving the desired level of robust performance exact tuning of rule base and membership functions are very important. The motivation for using the GA and PSO as a hybrid method are to reduce fuzzy effort and take large parametric uncertainties in to account. This newly developed control strategy mixed the advantage of GA and PSO techniques to optimally tune the rule base and membership function parameters of fuzzy controller that leads to a flexible controller with simple structure while is easy to implement.

Keywords:

PID , GA , Rule Base , PSO , Multi machine System , Fuzzy , Membership function