Abstract

Modular multilevel converters (MMC) have the characteristics of high modularity, good availability and high-power quality. Thus, they are widely used in medium and high-power applications. To meet large capacity application requirements, a large number of capacitors is applied in parallel and series. However, capacitors are one of the most vulnerable components in MMCs. To identify abnormal capacitors, a condition monitoring method for capacitors is proposed in this paper using the cumulative sum detection of the sliding window algorithm. First, the bilateral cumulative sum algorithm of the sliding window is proposed to extract the switch-on time and switch-off time of the submodules (SMs). Second, the capacitance is calculated using the monitored capacitor voltage and arm current during the switch-on status. Finally, the accuracy and effectiveness of the proposed method are verified by an MMC system operating condition simulated experiment platform. The proposed condition monitoring method simplifies the calculation of capacitance with a high accuracy by removing the requirement of measuring the switching signal. In addition, it does not have an adverse influence on the normal operation of MMC systems.

中文翻译：

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基于滑窗累加和检测的模块化多电平变流器子模块电容器在线监测方法

摘要

模块化多电平变换器（MMC）具有模块化程度高、可用性好、电能质量高等特点。因此，它们广泛用于中功率和高功率应用。为了满足大容量的应用要求，大量电容器并联和串联应用。然而，电容器是 MMC 中最容易损坏的组件之一。为了识别异常电容器，本文提出了一种利用滑动窗口算法的累积和检测的电容器状态监测方法。首先，提出滑动窗口双边累加和算法来提取子模块（SM）的开启时间和关闭时间。其次，使用接通状态期间监测的电容器电压和臂电流来计算电容。最后通过MMC系统工况模拟实验平台验证了该方法的准确性和有效性。所提出的状态监测方法通过消除测量开关信号的要求，简化了高精度电容的​​计算。另外，也不会对MMC系统的正常运行产生不利影响。