Modulated Model Predictive Control for MMC-Based Active Front-End Rectifiers Under Unbalanced Grid Conditions

Abstract

Modular multilevel converters (MMCs) have been widely used in recent years due to their superior advantages in medium/high-voltage applications. The finite control set model predictive control (FCS-MPC) has shown high dynamic responses for the control of the MMC. However, with the existing FCS-MPC algorithms, the steady-state performances are degraded due to the irregular pulse patterns, especially under unbalanced grid conditions. In this paper, based on the discrete state-space model of the MMC, a modulated MPC (M2PC) algorithm is proposed to overcome the aforementioned drawback of the FCS-MPC. Compared to FCS-MPC algorithms, the M2PC accurately calculates and tracks the reference circulating current and adopts an effective modulation method, and, in turn, the proposed M2PC can obtain enhanced steady-state ac-side/circulating currents control performances under unbalanced grid conditions, with the high dynamic-state performances of the conventional FCS-MPC algorithms reserved. Experimental results regarding one typical FCS-MPC algorithm and the proposed M2PC algorithm are comparatively evaluated in detail for the steady/dynamic-state performances and pulse patterns by a downscaled prototype. The effectiveness and feasibility of the proposed M2PC are clearly validated by the experimental results.