基于卡尔曼滤波的模块化多电平变换器模型预测控制方法

Yufei Yue, Xi Yang, Wen Wang, Xin Tang, Peng Guo
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引用次数: 0

摘要

针对输出电流跟踪、电容电压平衡、谐波循环电流抑制同步控制以及传感器调节模块化多电平变换器(MMC)损坏对系统运行可靠性的影响,提出了一种基于卡尔曼滤波(MPC-KF)的模型预测控制方法,旨在实现多目标控制,提高MMC系统的运行可靠性。首先,介绍了MMC的MPC原理。在此基础上,提出了一种基于卡尔曼滤波的电容电压预测校正策略,采用单臂电流传感器来获取电容电压校正值,而不是使用大量的子模块电压传感器。从这个意义上说,可以提高系统在传感器故障下的可靠性。最后,通过与单电压传感器的SM电压估计策略和传统的SM电容电压测量策略的比较,通过仿真研究验证了所提出的MPC-KF方法在MMC中的可行性和有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Model Predictive Control Method for Modular Multilevel Converter Based on Kalman Filter
This paper proposes a model predictive control method based on Kalman filter (MPC-KF) for solving the challenges in simultaneous control of output current tracking, capacitor voltages balance, and harmonic circulating currents suppression, and the operation reliability affected by the damaged sensors regulated modular multilevel converter (MMC), which aims to realize the multi-objective control, enhancing the operation reliability of MMC system. Firstly, the MPC principle of MMC is described. Then, the capacitor voltage prediction-correction strategy based on Kalman filter with only arm current sensor is proposed to obtain the capacitor voltage correction value, instead of using lots of submodule(SM) voltage sensors. In this sense, the reliability under sensor failures of system can be improved. Finally, compared with the SM voltage estimation strategy with single voltage sensor and the conventional SM capacitor voltage measurement strategy, simulation studies are illustrated to demonstrate the feasibility and effectiveness of the proposed MPC-KF method for MMC.
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