COMPARATIVE MATLAB-BASED ANALYSIS OF PI, PID, AI-PI AND AI-PID CONTROLLERS FOR INVERTER DYNAMIC PERFORMANCE UNDER EV PENETRATION VARIATIONS

The increasing penetration of electric vehicles (EVs) introduces important dynamic stability challenges to inverter-based smart grid systems. Rapid EV charging demand variations reduce system damping and increase oscillatory behavior, negatively affecting transient performance. This study presents a comparative MATLAB-based analysis of PI, PID, AI-PI, and AI-PID controllers under different EV penetration levels. The controllers are evaluated using overshoot, settling time, rise time, disturbance rejection, Integral Squared Error (ISE), Integral Time Absolute Error (ITAE), and control effort metrics. Simulation results show that increasing EV penetration significantly degrades inverter dynamic stability. Although the AI-PI controller improves transient response speed, it produces excessive overshoot under high EV loading conditions. The proposed AI-PID controller achieves the best overall performance by reducing overshoot, improving disturbance rejection capability, and minimizing error indices. The results demonstrate that AI-assisted adaptive PID control can significantly improve inverter robustness and transient stability in EV-integrated smart grids.