Model-predictive control of grid-connected inverters for PV systems with flexible power regulation and switching frequency reduction

This paper presents a model-predictive direct power control (MPDPC) strategy for a grid-connected inverter used in a PV system. Thus is aimed at use in distributed generation. The controller uses a system model to predict the system behavior at each sampling instant. The voltage vector generating least power ripples will then be selected according to a cost function and applied during the next sampling period, thus flexible power regulation can be achieved. In addition, the influences of one-step delay in digital implementation is investigated and compensated using a model based prediction scheme. Furthermore, a switching frequency reduction algorithm is developed by adding a nonlinear constraint to the cost function, which is a significant advantage in higher-power applications. The effectiveness of the proposed MPC strategy was verified numerically by using MATLAB/Simulink, and validated experimentally using a laboratory prototype.