Three-Layer Simplified Predictive Control to Enhance Performance of Dual-Parallel 5L-ANPC Inverters

Abstract

With the increasing dc-bus voltage level and power rating in renewable-energy applications, dual-parallel five-level active neutral-point-clamped (5L-ANPC) inverters have attracted growing attention because they can increase system capacity and improve output current quality. However, under asynchronous strategy, the dual-parallel 5L-ANPC inverters face a large number of space voltage vectors. Meanwhile, the simultaneous requirements of current tracking, CMV reduction, circulating current suppression, and capacitor voltage balancing further increase the difficulty of multi-objective control. To address these issues, this paper proposes a three-layer simplified model predictive control (MPC) strategy. The dual-parallel system is regarded as an equivalent nine-level inverter to improve the output current quality. To avoid the heavy burden caused by the large space voltage vector diagram, the gh coordinate system is adopted to calculate the required vector coordinates online, and low-CMV vector states are further selected to synthesize the reference voltage ( $V_{ref}$ ) without lookup tables (LUT). Then, a dynamic circulating current control strategy is developed to reallocate the vector states of each 5L-ANPC inverter, so that differential-mode current (DMCC) and zero-sequence circulating current (ZSCC) can be suppressed even under conditions of severe inductance mismatch. Finally, redundant switching combinations are used to balance the floating capacitor voltage (FCV) and neutral-point voltage (NPV). Experimental results show that compared with the advanced synchronous MPC strategy, the proposed strategy reduces the CMV peak-to-peak value by half, decreases the CMV RMS by up to 50%, and lowers the output current THD by at least 25%.