In power systems, Low Frequency Oscillations (LFO) in the range of 0.1-2.5 Hz have been solved through Power System Stabilizer (PSS). Proportional Integral Derivative (PID) controller is the simplest and effective solution to the most of control engineering applications today. Based on advantage, the PID controller combined with PSS to enhance the stability in power system. In practice most of the PID controller and parameters of PSS are tuned manually and fixed for certain operating conditions. In general power systems are non linear, conventional methods had lack of robustness. Therefore it is necessary to take advantage in simplifying the problem and implementation by utilizing most efficient optimization methods. From this view, many optimization methods and algorithms have been employed to tune the PID gains and PSS parameters. This paper broadly reviews the optimization methods and algorithms such as Conventional methods, Soft Computing, Genetic Algorithm (GA), Evolutionary Programming (EP), Differential Evolution (DE) and Swarm Intelligence methods were available for tuning the PID gains and PSS parameters successfully. Research showed the design of controllers based on conventional methods; soft computing and population based algorithms suffer from limitations. However, swarm intelligence techniques proved to be able to overcome these limitations. Swarm intelligence based coordinated controller (PID+PSS), will effectively enhance the small signal stability and transient stability in power system. An effort is made in this paper to present a broad analysis of tuning the PID gains and PSS parameters by various researchers.
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