模块化多电平变换器的分布式事件触发一致性控制

Anant Kumar Verma;Rodrigo Zuloaga;Héctor Matías Levis Calluil;Manuel Martinez-Gomez;Claudio Burgos-Mellado;Miguel A. Torres
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引用次数: 0

摘要

模块化多电平转换器(MMC)是一种突出的拓扑结构,适用于中高压、大功率转换应用。该转换器具有基于称为子模块(SMs)的构建块的模块化构造。然而,典型应用程序中所需的大量SMs使得通过集中控制体系结构操作MMC变得困难。近年来,人们提出了分布式控制方案,为MMC提供模块化的硬件和软件开发解决方案。这种控制体系结构允许两级层次结构,其中在转换器SMs中的本地控制器(lc)之间有分布的低级控制任务,而中央控制器(CC)承担高级控制任务。在这种方案下,lc和CC都可以在不同的时间步长执行他们的控制算法,优化控制硬件利用率:这在以前的MMC中没有报道过使用分布式控制方法。在此基础上,本文提出了一种事件触发分布式控制方案来调节MMC中的电容电压。与之前报道的工作相反,该提案仅在触发事件发生时更新LCs的控制动作,显著降低了LCs的硬件利用率。实时硬件在环仿真研究验证了该方案的有效性,并将其性能与传统的基于共识的分布式方案进行了比较,显示出优越的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Distributed Event-Triggered Consensus Control for Modular Multilevel Converters
The modular multilevel converter (MMC) is a prominent topology for medium to high-voltage, high-power conversion applications. This converter has a modular construction based on building blocks named submodules (SMs). However, the large number of SMs required in a typical application makes operating the MMC through a centralized control architecture difficult. Recently, distributed control schemes have been proposed to provide a modular hardware and software development solution for the MMC. This control architecture allows a two-level hierarchy, in which there are distributed low-level control tasks among local controllers (LCs) placed in the converter SMs, while central controller (CC) undertakes high-level control tasks. Under this scheme, both LCs and the CC could execute their control algorithms at different time steps, optimizing the control hardware utilization: this has not been previously reported for MMC operating with a distributed control approach. Based on that, this article proposes an event-triggered distributed control scheme for regulating the capacitor voltages in the MMC. Contrary to previously reported works, the proposal only updates the control actions of LCs when a trigger event occurs, notably reducing the LCs hardware utilization. Real-time hardware-in-the-loop simulation studies validate the proposal's effectiveness, and its performance is compared with traditional consensus-based distributed approach, showing superior performance.
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