一种新的三相系统状态空间模型的卡尔曼滤波:在对称分量辨识中的应用

A. Phan, Gilles Hermann, P. Wira
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引用次数: 10

摘要

在电能传输挑战中,电能质量问题,如减少谐波污染,无功功率和负载不平衡,必须以快速和精确的方式识别三相的对称分量。为了实时估计失真时变电力系统的对称分量,本文提出了一种新的状态空间模型,并将其与扩展卡尔曼滤波器(EKF)结合使用。因此,所提出的模型能够检测和量化一般三相电力系统的不平衡。事实上,电力系统的对称分量,即它们的振幅和相位角值,可以在每次迭代中从所提出的状态空间模型中推导出来。对该方法的有效性进行了评价。在线对称分量辨识的结果和比较表明了该方法对扰动变化电力系统的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Kalman filtering with a new state-space model for three-phase systems: Application to the identification of symmetrical components
In electrical energy transportation challenges, power quality issues like reducing harmonic pollution, reactive power and load unbalance, necessarily have to identify the symmetrical components of the three phases in a fast and precise way. This paper introduces a new state-space model to be used with an Extended Kalman Filter (EKF) in order to estimate in real-time the symmetrical components of distorted and time-changing power systems. The proposed model is therefore able to detect and to quantify the unbalance of general three-phase power systems. Indeed, the symmetrical components of the power system, i.e., their amplitude and phase angle values, can be deduced at each iteration from the proposed state-space model. The effectiveness of the method has been evaluated. Results and comparisons of online symmetrical components identification show the efficiency of the proposed method for disturbed and changing power systems.
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