Sliding Mode-based Model Predictive Control of Grid-Forming Power Converters

Grid-forming (GFM) converters are becoming an inevitable component of AC power systems due to the growing demand for distributed energy resources. However, enhancing their performance is still a critical challenge. Conventional dual-loop proportional-integral (PI) control structures are usually used to control a GFM inverter in a dq reference frame. However, they experience unbalancing in transient and steady-state performance. This paper proposes a sliding-mode control (SMC) based finite control set model predictive control (FCS-MPC) for voltage control of a GFM inverter in a grid-connected mode. The SMC is presented for the adaptive and optimal determination of the weighting factors in FCS-MPC. The proposed strategy's key benefit is the SMC's real-time execution. By doing this, the weighting factors are constantly updated in real-time, which avoids the dependence of the response of the inverter control system under uncertainties and external disturbances. Furthermore, to accurately track power references and deliver the required virtual inertia, a virtual synchronous generator controller is utilized to implement the active power loop. The suggested approach has been shown to be effective based on the simulation results when compared to a dual-loop PI control method.