Passivity-Based Inverse Model Predictive Control With Reduced Sensors for Grid-Forming Inverters

This article proposes a novel control strategy for grid-forming inverters based on passivity principles and inverse model predictive control (IMPC). The principle of passivity-based control is utilized to reduce the number of required measurements, which enhances the reliability, simplifies the design, and reduces the cost of the control system. Moreover, the proposed approach is generalized to operate reliably even when any group of sensors is unavailable, provided that the other three sensor groups remain available. The sensor groups typically include inverter-side current sensors, filter capacitor voltage sensors, grid-side current sensors, and grid-side voltage sensors. Furthermore, the IMPC technique is employed to control the inverter states effectively, with minimal computational overhead. A key advantage of this approach lies in its ability to generate optimal control signals with a reduced number of sensors, which makes IMPC both optimal and cost-effective. The proposed controller is experimentally validated in multidistributed generation scenarios and is benchmarked against the conventional MPC to demonstrate its effectiveness.