Particle Swarm Optimization Based LFC and AVR of Autonomous Power Generating System

Abstract

In this paper, an evolutionary computing approach for determining the optimal values for the proportional-integral- derivative (PID) controller parameters of load frequency control (LFC) and Automatic Voltage Regulator (AVR) system of single area power system using the particle swarm optimization technique is presented. The LFC loop controls real power & frequency and AVR loop controls reactive power and voltage. Due to rising and falling power demand, the real and reactive power balance is harmed; hence frequency and voltage get deviated from nominal value. This necessitates designing of an accurate and fast controller to maintain the system parameters at nominal value. The main purpose of system generation control is to balance the system generation against the load and losses so that the desired frequency and power interchange between neighboring systems are maintained. This work demonstrates the application of PSO method to search efficiently optimal PID controller parameters of LFC and AVR system. The proposed method had superior features like, stable convergence characteristics, easy implementation and good computational efficiency. The simulation results demonstrate the effectiveness of the designed system in terms of reduced settling time, overshoot and oscillations. The results are compared with conventional PID , Fuzzy and GA based controllers.