Three-Phase Model-Based Predictive Control Methods With Reduced Calculation Burden for Modular Multilevel Converters

Kennel, Ralph

Abstract

Model predictive control (MPC) has been widely investigated in modular multilevel converters (MMCs) due to its superiority in achieving multiple control objectives. The three-phase model-based MPC, which contains the common-mode voltage in the output current dynamic model and considers interaction among phases, shows better performance than the conventional per-phase model-based predictive control in a three-phase MMC system. However, it suffers from a heavy computational burden as the number of submodules (SMs) increases. To address this issue, this article first analyzes the relationship among the numbers of inserted SMs, the controllability of dc-link current, and circulating currents. Then, according to this analysis, two simplified MPC methods based on the three-phase model with reduced computational burden are proposed. Specifically, fewer insertion index combinations are selected in advance to ensure good output currents, controllable dc-link, and circulating currents. The effectiveness of the proposed methods is verified through experimental results.

Más información

Título según WOS: Three-Phase Model-Based Predictive Control Methods With Reduced Calculation Burden for Modular Multilevel Converters
Título de la Revista: IEEE JOURNAL OF EMERGING AND SELECTED TOPICS IN POWER ELECTRONICS
Volumen: 10
Número: 6
Editorial: IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Fecha de publicación: 2022
Página de inicio: 7037
Página final: 7048
DOI:

10.1109/JESTPE.2022.3170503

Notas: ISI