Analysis of Genetic Algorithm-Optimized PID Controllers for a Two-Area Automatic Generation Control System

Abstract

This paper aims to analyze an interconnected two-area Automatic Generation Control (AGC) power system through the application of optimization techniques based on Genetic Algorithm (GA). The principal objective is to enhance the overall system performance by optimizing the gain values of the three PID controllers using advanced optimization techniques like GA. This paper explores the overall performance by analyzing settling times in areas one and two and the deviation in tie line power. The system error is effectively minimized through the optimization of GA with the objective function of Integral Time Absolute Error (ITAE). Comparative analyses are conducted, comparing settling times in each area, tie line power deviation, and ITAE values with earlier simulated studies for a more comprehensive understanding to evaluate the novelty. The system is analyzed under two distinct loading conditions, analyzing each scenario individually in a case-by-case analysis. The article highlights the significance of the two-area AGC system and emphasizes the role of optimization techniques in elevating its performance, elucidating the substantial impact that optimization methods can bring