Comparative Analysis of Load Frequency Control Under Multi-Disturbance in Renewable-Integrated Power Systems

Abstract

Load frequency control (LFC) is essential for maintaining frequency stability and reliable operation in modern power systems, particularly with increasing penetration of renewable energy sources, where reduced system inertia and stochastic power fluctuations pose significant challenges to conventional control strategies. This study develops a single-area LFC model in MATLAB/Simulink. It presents a comparative evaluation of conventional linear controllers, namely proportional–integral (PI) and proportional–integral–derivative (PID) controllers, alongside advanced control strategies comprising fuzzy logic control (FLC), fractional-order proportional–integral–derivative (FOPID) control, and an adaptive neuro-fuzzy inference system (ANFIS). The controllers are evaluated under multiple disturbance conditions, including step load changes, renewable power fluctuations, random load variations, measurement noise, and fault events. Their performance is assessed using peak frequency deviation, which means frequency deviation, root-mean-square error, and the integral of time-weighted absolute error. The comparative analysis demonstrates that advanced controllers generally provide better frequency regulation and disturbance rejection than conventional PI and PID controllers. Among the investigated approaches, ANFIS exhibits the strongest overall performance across the disturbance scenarios considered, while FOPID and fuzzy logic control also demonstrate improved dynamic responses under specific operating conditions. These findings indicate that advanced control strategies can enhance damping, robustness, and frequency regulation in the investigated renewable-integrated power system and highlight the potential of intelligent control techniques for power systems operating under variable and uncertain conditions.