Grouping-sorting optimized model predictive control of modular multilevel converter with reduced computational load

Modular Multilevel Converter (MMC) is a promising topology for high voltage/power AC/DC and DC/AC applications. Model Predictive Control (MPC) is an advanced and simple method for power converters control. However, its computational load becomes unacceptable when MMC voltage level increases. Although an optimized MPC proposed for the MMC decreased the number of the possible actuations of each phase from C_2N^N to N+1 for N+1 levels MMC, which is still difficult for application as the number of submodule for each arm reached hundreds. The Grouping-Sorting algorithm optimized MPC (GSOMPC) is proposed in the paper. The submodule capacitor voltages within the group and among groups are sorted according to the arm current polarity, the proposed GSOMPC decreased the number of the possible actuations of each phase from N+1 to 2X+M+3 (N=M×X) for N+1 levels MMC. The simulation and experimental results based on 25-level MMC verify the correctness and effectiveness of the GSOMPC strategy.