Multi Machine Power System Stabilizer Design Using Particle Swarm Optimization Technique

In this paper, multi objective design of multi-machine Power System Stabilizers (PSSs) using Particle Swarm Optimization (PSO) is presented. The stabilizers are tuned to simultaneously shift the lightly damped and undammed electro-mechanical modes of all machines to a prescribed zone in the s-plane. A multi objective problem is formulated to optimize a composite set of objective functions comprising the damping factor, and the damping ratio of the lightly damped electromechanical modes. The PSSs parameters tuning problem is converted to an optimization problem which is solved by PSO with the eigen value-based multi objective function. The proposed PSO based PSSs is tested on a multi machine power system under different operating conditions and disturbances through eigen value analysis and some performance indices to illustrate its robust performance. The eigen value sensitivity analysis has been used for PSS design in many literatures under deterministic system operating conditions. To consider the effect of more system operating factors, the technique of probabilistic eigen value analysis was proposed and has been applied for the parameter design of power system damping controllers. In the probabilistic eigen value analysis the system stability is enhanced by shifting the distribution ranges of the critical eigen values to the left side of the complex plane. A new approach for the optimal decentralized design of PSSs with output feedback is investigated in.