Optimization Techniques Based Power System Stabilizer’s: An Overview

Low frequency oscillation problems are very difficult to solve because power systems are very large, complex and geographically distributed. Therefore, it is necessary to utilize most efficient optimization methods to take full advantages in simplifying the problem and its implementation. From this perspective, many successful and powerful optimization methods and algorithms have been employed in formulating and solving this problem.This paper reviews new approaches in modern research using optimization techniques to develop power system stabilizer (PSS These techniques are such as Tabu search (TS), simulated annealing (SA), Ant Colony Optimization (ACO), Harmony search (HS), evolutionary programming (EP), bacteria foraging optimization (BFO), genetic algorithm (GA), particle swarm optimization (PSO) Bee colony, Artificial Bee Colony (ABC), SFLA algorithm, etc have been used. Research showed controllers designed based on a conventional control theory, modern and adaptive control theories, suffer from some limitations. However, Optimization techniques proved to be able to overcome theses limits. Hence, more researchers preferred to utilize these approaches for the power systems. The review efforts geared towards PSS developed based on Optimization techniques, which effectively enhance both small signal stability and transient stability and equally provide superior performances. In this paper a serious attempt is made to present a comprehensive analysis of optimization techniques for designing PSSs, which were recently proposed by various researchers.