Associate Professor Yang Xingwu's research team at Shanghai University of Electric Power has proposed a new two-stage model predictive control method to reduce computation and increase the output voltage level to 2N+1. The discrete-time mathematical model of modular multilevel controller was first derived, and two circulating factors were introduced to directly calculate the optimal voltage difference and sum of the bridge arm, so as to determine the optimal number of submodules for upper and lower bridge arms in the first-stage control. In the second-stage control, based on the optimal number of submodules determined in the first-stage control, upper and lower bridge arms were adjusted by adding or subtracting one submodule, forming an array of optimization options that were then put into the objective function to select the submodule with the lowest objective function value for investment, thereby determining the final investment in MMC. Both first-stage control and second-stage control avoided the selection of weight factors. Finally, the RSF algorithm was applied to control the submodule capacitor voltage and reduce the switching frequency. The research used the StarSim real-time simulator for power electronics with small time steps provided by ModelingTech to experimentally verify the effectiveness of the proposed method, and the results were summarized and published in : Yang X, Liu H, Mi Y, Ji L, Wang Y, Fu Y. An improved two-stage model predictive control method for modular multilevel converter. IET Electr. Power Appl. 2021;1–12.