Grid Voltage Sensor-Less State-Observer based OSS-MPCC for Grid-Tied Inverter with LCL Filter

This paper presents an enhanced reduced-sensor Optimal-Switching-Sequence Model-Predictive-Current-Control (OSS-MPCC) algorithm for grid-tied inverters with LCL filters, using only injected grid current measurements. The OSS-MPCC algorithm relies on four signals: estimated symmetrical components of grid voltage from a virtual flux observer, state estimates from Kalman Filter based estimation, reference positive sequence grid current from SOGI-QSG symmetrical voltage estimations, and inverter switching states for predictive current tracking. The proposed algorithm offers multiple benefits: it limits the switching frequency spectrum of the inverter voltage, reduces sensor count from nine to three, maintains low grid current THD even with voltage unbalance, and its computational time is comparable to previous OSS-MPC algorithms. Numerical validation has been conducted through MATLAB simulations.