王禹, 胡辉勇, 于淼, 韦巍. 三相电网信号的双重Kalman滤波测量方法[J]. 电力系统自动化, 2017, 41(16): 171-178.
引用本文: 王禹, 胡辉勇, 于淼, 韦巍. 三相电网信号的双重Kalman滤波测量方法[J]. 电力系统自动化, 2017, 41(16): 171-178.
WANG Yu, HU Huiyong, YU Miao, WEI Wei. Measurement Method of Dual Kalman Filtering for Three-phase Grid Signals[J]. Automation of Electric Power Systems, 2017, 41(16): 171-178.
Citation: WANG Yu, HU Huiyong, YU Miao, WEI Wei. Measurement Method of Dual Kalman Filtering for Three-phase Grid Signals[J]. Automation of Electric Power Systems, 2017, 41(16): 171-178.

三相电网信号的双重Kalman滤波测量方法

Measurement Method of Dual Kalman Filtering for Three-phase Grid Signals

  • 摘要: 提出一种基于Kalman滤波器的三相电网信号的谐波分析方法。该算法针对正负序分量的幅值相位和基波的频率,分别建立一个Kalman滤波器,并在两个滤波器之间形成联系。前者的状态变量可以用来计算基波瞬时频率并作为后者的测量;后者的状态变量可以提供前者模型参数。给出了两个滤波器的初始化过程与检测信号突变的方法,从而加快算法的响应速度。仿真验证了三相电网信号的幅值、相位和频率发生突变,幅值和频率同时连续变化,以及处于三相不平衡条件下,双重Kalman滤波测量方法依然准确高效。实验对非理想电网的三相电压、电流信号进行谐波分析,根据分析结果重构的信号误差平均值分别仅为0.67%和1.04%。

     

    Abstract: A Kalman filter based method is proposed for the harmonics analysis of three-phase grid signals. The method sets up two Kalman filters, one of which works for the estimation of harmonics’ amplitude and phase, and the other for the estimation of fundamental frequency. The relationships between these two Kalman filters are described. The state estimate of the former can be used to calculate the measurement of the latter and the state estimate of the latter provides model frequency to the former. To accelerate the algorithm,the initialization of Kalman filters and an algorithm for detecting the abrupt change in signals are presented. It is verified by simulation that the proposed method is still highly efficient with abrupt changes in three-phase grid signals, in amplitude, phase and frequency,with continuous changes in amplitude and frequency, and under unbalanced conditions. The experiment applies the proposed method to the voltage and current signals of a three-phase motor under non-ideal grid conditions, where the mean relative errors between the reconstructed signal and the original one are only 0. 67% and 1. 04%, respectively.

     

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