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Harmonics Estimation of a Noisy Power System Signal Using Cubature Kalman Filter

机译:使用Cubature卡尔曼滤波器的电力系统噪声谐波估计。

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Fast and accurate estimation of harmonics of a typical power system signal is very much desirable for power quality assessment. This paper proposes an application of the cubature Kalman filter (CKF)for estimating the parameters of harmonics, sub-harmonics, and inter-harmonics of a signal in presence of noise. CKF utilizes a third-degree spherical radial cubature rule to estimate the probability density functions of the states as well as the measurements. At the same time, this technique does not require any linearization and saves the computational time. The effectiveness of CKF has been compared with UKF by performing various test cases. It is observed from the simulation results that CKF exhibits superior performance in estimating the parameters of harmonics, inter-harmonics, and sub-harmonics of a distorted power system static as well as the dynamic signal by virtue of execution time and accuracy.
机译:对于电能质量评估,非常需要快速而准确地估算典型电力系统信号的谐波。本文提出了一种使用库曼卡尔曼滤波器(CKF)来估计存在噪声的信号的谐波,次谐波和间谐波的参数的应用。 CKF利用三次球面径向容积法则来估计状态和测量的概率密度函数。同时,该技术不需要任何线性化,并节省了计算时间。通过执行各种测试案例,已将CKF的有效性与UKF进行了比较。从仿真结果可以看出,CKF在执行时间和准确性方面,在估计畸变的电力系统静态和动态信号的谐波,间谐波和次谐波的参数方面表现出优异的性能。

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