Hierarchical Feedback Model Predictive Control for HVDC-MMC with Low Computation Burden

Abstract

Model Predictive Control (MPC) methods are suitable for modular multilevel converters (MMCs) due to their multi-objective control capability and fast dynamic response. But the weighting factors of the cost function are difficult to tune appropriately and need extensive simulation and experimental tests. This paper proposes a model predictive control strategy based on hierarchical feedback. By establishing the feedback mechanism between alternating current and circulating current control, the number of inserted submodules (SMs) of upper and lower arms are quickly determined to realize the optimal control of multiple objectives, and the tuning process of the weighting factors is eliminated. The computation burden of the cost function is reduced by the preselection of the inserted SMs combination. MPC with the Hierarchical Feedback control can generate $2N+1$ output voltage level in the MMC while suppressing the circulating current. Finally, an MMC-HVDC system has been developed to verify the validity and effectiveness of the proposed method.