Modular Multilevel Converters (MMCs) Controlled by Model Predictive Control With Reduced Calculation Burden

Abstract

Model predictive control (MPC) for modular multilevel converter (MMC) systems has drawn attention among researchers in recent years due to its straightforward implementation, ability to control multiple objectives in a single cost function, and excellent dynamic response. Even though MPC seems promising for the MMC, it suffers from an excessive increase in computational complexity when the number of submodules (SMs) per arm (N) is increased. The computational load can be reduced by decoupling the SM capacitor voltage control from the cost function and balancing them in an external voltage sorting algorithm. In this paper, a further reduction of computations in the MPC is achieved by the preselection of control options that can satisfy the control objectives in the next sampling time. The preselection algorithm generates a greatly reduced number of control options to be computed by a straightforward MPC loop at each sampling time. In addition, the MPC together with the preselection algorithm can generate 2N + 1 output voltage levels in the MMC while maintaining a low dv/dt in the output voltage and suppressing the circulating currents in MMCs with considerable number of SMs. The steady-state and dynamic performance of the MMC operating with the proposed method is verified by simulation and experimental results.