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A Low-Computation Indirect Model Predictive Control for Modular Multilevel Converters
Wenzhong Ma, Peng Sun*, Guanyu Zhou**, Gulipali Sailijiang**, Ziang Zhang**, and Yong Liu***
Abstract The modular multilevel converter (MMC) has become a promising topology for high-voltage direct current (HVDC) transmission system. To control the MMC system properly, the ac-side current, circulating current, and submodule (SM) capacitor voltage are taken into consideration. This paper proposes a low-computation indirect model predictive control (IMPC) strategy that takes the advantage of conventional MPC and has no weight factors. The cost function and duty cycle are introduced to minimize the tracking error of ac-side current and eliminate the circulating current. An optimized merge sort (OMS) algorithm is applied to maintain the SM capacitor voltages balanced. The proposed IMPC strategy effectively reduces the controller complexity and computation burden. In this paper, a discrete-time mathematical model of the MMC system is developed and the duty ratio of switching state is designed, respectively. In addition, a simulation of an eleven-level MMC system based on MATLAB/Simulink and a five-level experimental setup are built to evaluate the feasibility and performance of the proposed low-computation IMPC strategy, respectively.
Keyword Current tracking, Circulating current control, Capacitor voltage balancing, Model predictive control, Modular multilevel converter
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