APPLYING PARTICLE SWARM OPTIMIZATION TO DESIGN ADAPTIVE FUZZY LOGIC LOAD-FREQUENCY CONTROLLERS FOR A LARGE-SCALE POWER SYSTEM

Abstract

Due to the continually time-by-time load variation, the working frequency and tie-line power flow in a large-scale power system will be deviated from their scheduled values. The most important objective of the Load-Frequency Control (LFC) strategy is to damp the oscillations of the frequency and tie-line power deviations to restore rapidly the steady state of the system. This paper focuses on designing a type of adaptive PI-based fuzzy logic (FL) load-frequency controllers, which can deal with the LFC problem in a complicated power system in reality. Scaling factors of such controller, which significantly impact on the control quality, will be optimized by applying the Particle Swarm Optimization (PSO) technique. Inspired by the biological evolutionary theory, the PSO method has been used successfully in many modern control schemes due to its great simplicity and efficiency. Hence, the proposed PSO-PI-based FL controllers can achieve the desired control properties when solving the LFC problem. Promising simulation results obtained in a typical test system can be used to validate the feasibility and superiority of the proposed control strategy in comparison with the conventional regulators using PID.