Virtual Vector Optimal Selection Strategy for NPC Three‐Level Grid‐Tied Converter with Finite Control Set Model Predictive Control

Abstract

Virtual vector is applied in neutral‐point‐clamped (NPC) three‐level converter finite control set model predictive control (FCS‐MPC) strategy due to its good performance of less current ripples and high power efficiency. However, in the process of adding virtual vectors, some redundant virtual vectors will be selected. Excessive virtual vector will increase the computational burden and affect grid‐tied current performance. A virtual vector optimal selection strategy for model predictive control to determine the vectors is proposed. The strategy calculates the fluctuation of grid‐tied current through theoretical analysis. Based on the analysis of amplitude fluctuation of grid‐tied current, the graphics of coverage angle visualization can be obtained under different virtual vector. The angle of the required virtual vectors is obtained through the graphics of coverage angle visualization. The number of virtual vector can be determined when the error current angle range covers the entire vector graph. The proposed control strategy was compared with the conventional control strategies, including excessive virtual vectors or with no any virtual vector. Experimental results show that the proposed control strategy can significantly reduce THD, grid‐tied current error and computational burden. © 2022 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC.