Enhancing Dynamic Performance through ANN-Assisted AGC System and Real-Time Energy Market Participation

Ensuring frequency stability and controlling active power are fundamental tasks in enhancing the security and reliability of power system operations. This paper investigates the influence of discrete secondary frequency controllers on the dynamic response of power systems, considering both conventional automatic generation control (AGC) and Market-based AGC (AGC<inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">M</inf>), also referred to as Real-Time Energy Market (RTEM). The study explores how integrating market-based dispatch mechanisms with Artificial Neural Networks (ANN)-assisted AGC systems enhances frequency regulation under dynamic operating conditions. In order to maintain stable operation, the frequency change caused by load variations must be brought as close to zero as possible. MATLAB-Simulink is utilized to simulate the ANN-based controller's performance under both step load and random load changes in the system. The results of the simulation have been compared and studied. The response characteristics of the ANN controller integrated with the conventional controller are compared with those of the integral and PID controllers to evaluate its performance in improving system dynamics.