Model predictive control of grid-connected NPC inverter with automatic weighting factors selection and reduced switching frequency

Li, M., Shu, Zhan and Chu, B. (2020) Model predictive control of grid-connected NPC inverter with automatic weighting factors selection and reduced switching frequency. In 2020 IEEE 9th International Power Electronics and Motion Control Conference, IPEMC 2020 ECCE Asia. IEEE. pp. 1043-1048 . (doi:10.1109/IPEMC-ECCEAsia48364.2020.9367661).

Record type: Conference or Workshop Item (Paper)

Abstract

A model predictive control (MPC) algorithm for NPC grid-connected inverters is proposed with automatic selection of weighting factors. The main objective of this proposed algorithm is to reduce switching frequency and to provide for the automatic selection of weighting factors without the need for trial-and-error across different dynamic working conditions. The algorithm can also achieve active power tracking and maintain neutral point balancing functionalities. These various objectives are achieved through the use of a modified, 3-part cost function and the adoption of a two-dimensional fuzzy logic control scheme. The effectiveness of the proposed algorithm is verified using the results of grid-connected NPC inverters simulation, which show that the switching frequency can be reduced by at least 30% when compared to conventional MPC methods

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