MODEL PREDICTIVE CONTROL OF GRID-CONNECTED PV INVERTERS FOR ENHANCED TRANSIENT AND VOLTAGE STABILITY

Abstract

High penetration of photovoltaic (PV) generation introduces significant challenges to power system voltage regulation and transient stability due to reduced system inertia and intermittent power injection. Conventional control strategies employed in grid-connected PV inverters, such as proportional–integral (PI) and vector control methods, exhibit limited dynamic performance under fast grid disturbances and weak grid conditions. This paper proposes a grid-supportive Model Predictive Control (MPC) strategy for PV inverters aimed at enhancing voltage stability and transient response during grid disturbances. The proposed MPC framework explicitly incorporates system constraints, multi-objective control goals, and predictive behaviour to regulate inverter output currents and voltages effectively. By enabling fast dynamic voltage support and improved disturbance rejection, the proposed approach enhances grid stability without additional hardware requirements. Simulation results under various transient scenarios, including voltage sags, load variations, and grid faults, demonstrate superior performance of the MPC-controlled PV inverter compared with conventional PI-based controllers in terms of voltage recovery time, overshoot, and total harmonic distortion (THD).