Particle Swarm Optimization in Fine Tuning of PID Fuzzy Logic Power System Stabilizer

Abstract

Power system stabilizer must be capable of providing appropriate stabilization signals over a broad range of operating Equation Chapter 1 Section 1conditions and disturbances. Traditional power system stabilizers rely on linear design methods. The main disadvantage with the classical PID controller is that it cannot successfully control a plant with strong non-linearities and various operating conditions. The design of conventional PID power system stabilizer is based on a linear approximation of a nonlinear power plant around the operating point. During a major disturbance such as a fault, the operating point of a power system drifts; conventional PID controllers do not work well under such conditions. It is shown in literature, that a non linear controller will be more effective under such conditions. The fuzzy PID controller is such a controller. To cover a wider range of operating conditions, fuzzy logic power system stabilizers are proposed. It is very important to appropriately tune the parameters used in FLPSS. These parameters are commonly determined by trial and error method, which is rather time consuming. In the present paper Particle Swarm Optimization is used to tune the parameters of FLPSS. The efficacy of the stabilizer is tested on a single machine infinite bus bar system for different operating conditions.