Comparative Study of Optimization Techniques and Fuzzy Logic Controller for Load Frequency Control in Hybrid Power System

Abstract

This study focuses on the Load Frequency Control (LFC) of an islanded Hybrid Power System (HPS) that comprises a Wind Energy System (WES), a Diesel Energy System (DES), and a Superconducting Magnetic Energy Storage System (SMES). The study presents the implementation of the latest optimization techniques and the conventional Fuzzy Logic Controller (FLC) to improve the profiles of power and frequency in the HPS. The optimized control parameters of Proportional-Integral-Derivative (PID) using five different optimization techniques namely Runge-Kutta Optimization (RUN), Reptile Search Algorithm (RSA), Particle Swarm Optimization (PSO), Ant-Lion Optimization (ALO), and Artificial Bee Colony (ABC) are presented. The controllers for the WES and the DES were employed to control the power output and frequency. The SMES is utilized to enhance the system’s power quality. A comparative analysis of the five optimization techniques and the FLC in terms of power and frequency control, time, and speed of optimization is presented. The results of the study show that the implementation of optimization techniques for LFC in an islanded HPS can effectively improve the power and frequency profiles of the system. The comparative analysis provides insights into the most effective optimization techniques for LFC in HPS.