Comparative study of optimization algorithms for enhancement of small signal stability by designing PSS for multi-machine power system

Power System Stabilizers (PSSs) are used in very large, complex & interconnected power system in order to damp out low frequency oscillations. Therefore, it is required to utilize most efficient optimization techniques to simplify the small signal stability problem. From this point of view, many successful and powerful optimization methods and algorithms have been employed in formulating and solving this problem. The comparison of performances of three advanced optimization techniques in tuning the parameters of PSS in a New England test system (10 Generator, 39 buses) is presented in this paper. The optimization algorithms considered in this paper for effective analysis and design of PSS for multi-objective, multi-machine power systems are: Social Spider Optimization (SSO), Genetic Algorithm (GA), and Particle Swarm Optimization (PSO). Robustness of proposed technique is analyzed over different type of operating conditions. It is observed that Social Spider Optimization (SSO) is performing better than the other two algorithms.