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Indirect Finite Control Set Model Predictive Control of Modular Multilevel Converters

机译:模块化多电平转换器的间接有限控制集模型预测控制

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The modular multilevel converter (MMC) is a potential candidate for medium/high-power applications, specifically for high-voltage direct current transmission systems. One of the main challenges in the control of an MMC is to eliminate/minimize the circulating currents while the capacitor voltages are maintained balanced. This paper proposes a control strategy for the MMC using finite control set model predictive control (FCS-MPC). A bilinear mathematical model of the MMC is derived and discretized to predict the states of the MMC one step ahead. Within each switching cycle, the best switching state of the MMC is selected based on evaluation and minimization of a defined cost function. The defined cost function is aimed at the elimination of the MMC circulating currents, regulating the arm voltages, and controlling the ac-side currents. To reduce the calculation burden of the MPC, the submodule (SM) capacitor voltage balancing controller based on the conventional sorting method is combined with the proposed FCS-MPC strategy. The proposed FCS-MPC strategy determines the number of inserted/bypassed SMs within each arm of the MMC while the sorting algorithm is used to keep the SM capacitor voltages balanced. Using this strategy, only the summation of SM capacitor voltages of each arm is required for control purposes, which simplifies the communication among the SMs and the central controller. This paper also introduces a modified switching strategy, which not only reduces the calculation burden of the FCS-MPC strategy even more, but also simplifies the SM capacitor voltage balancing algorithm. In addition, this strategy reduces the SM switching frequency and power losses by avoiding the unnecessary switching transitions. The performance of the proposed strategies for a 20-level MMC is evaluated based on the time-domain simulation studies.
机译:模块化多电平转换器(MMC)是中/高功率应用(特别是高压直流输电系统)的潜在候选者。 MMC控制中的主要挑战之一是在保持电容器电压平衡的同时消除/最小化循环电流。本文提出了一种使用有限控制集模型预测控制(FCS-MPC)的MMC控制策略。推导并离散化了MMC的双线性数学模型,以预测MMC的状态。在每个开关周期内,基于对定义成本函数的评估和最小化,选择MMC的最佳开关状态。定义的成本函数旨在消除MMC循环电流,调节臂电压并控制交流侧电流。为了减轻MPC的计算负担,将基于常规排序方法的子模块(SM)电容器电压平衡控制器与所提出的FCS-MPC策略相结合。提出的FCS-MPC策略确定了MMC每个分支中插入/旁路SM的数量,同时使用排序算法来保持SM电容器电压平衡。使用此策略,仅需要每个臂的SM电容器电压的总和即可用于控制目的,从而简化了SM与中央控制器之间的通信。本文还介绍了一种改进的开关策略,它不仅可以减轻FCS-MPC策略的计算负担,而且可以简化SM电容器电压平衡算法。此外,该策略通过避免不必要的开关转换来减少SM开关频率和功率损耗。基于时域仿真研究,评估了针对20级MMC提出的策略的性能。

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