Enhancing automatic generation control in renewable energy-integrated thermal power systems with a novel PID+I λ controller tuned by INFO algorithm

Abstract

Electrical systems need to balance generation and demand to ensure that customers are supplied with safe and high-quality electricity. Failure to maintain this balance may result in unwanted frequency oscillation and, accordingly, tie-line power variation. Automatic generation control (AGC) is an important mechanism for controlling system responses and keeping them within predetermined bounds. Integrating renewable energy sources (RESs) into the grid can be complicated due to their erratic and weather-dependent nature, leading to imbalances in generation and consumption. To reduce these disparities, this study focuses on developing a novel proportional–integral–derivative (PID)+I^λ controller for the AGC in a two-area thermal power system utilizing wind turbines and photovoltaic (PV) panels as renewables. For achieving the best possible performance, the controller parameters are optimized using the weighted mean of vectors (INFO) algorithm. Simulation studies are conducted to evaluate the performance of the proposed controller under different load demands and RES scenarios. Comparative studies are also conducted to evaluate the true efficacy of the INFO-tuned PID+I^λ controller against some published control schemes available in the literature. It is found that our proposal outperforms its rivals in mitigating the unwanted system oscillations, lessening the overshoot/undershoot, and shortening the settling time of frequency and tie-line power responses.