Kalman Filtering with Harmonics Whitening for P Class Phasor Measurement Units

A. Bashian, D. Macii, D. Fontanelli, D. Petri
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Abstract

The need for increasingly accurate and fast Phasor Measurement Units (PMUs), especially for active distribution systems monitoring, requires to achieve challenging trade-offs between measurement uncertainty and responsiveness. This is particularly important for protection-oriented (i.e., P Class) PMUs. In order to improve estimation accuracy with no need to prolong the data record size and the related delays, this paper presents a Taylor Kalman Filter (TKF) enhanced with a preliminary stage able to whiten possible narrowband disturbances over short observation intervals. The use of dynamic estimators such as the TKF is motivated by the need to track possible sudden amplitude or phase changes of voltage or current AC waveforms, which are likely to occur in smart grids. However, while a basic TKF is very sensitive to disturbances different from white noise, the proposed whitening-technique is able to greatly improve the estimation accuracy of synchrophasor amplitude, phase, frequency and Rate of Change of Frequency (ROCOF) under the influence of harmonics and amplitude or phase step changes even over one-cycle observation intervals, with just a minor performance degradation in the other P Class testing conditions reported in the IEEE/IEC Standard 60255-118-1:2018.
P类相量测量单元的谐波白化卡尔曼滤波
对越来越精确和快速的相量测量单元(pmu)的需求,特别是对于主动配电系统监测,要求在测量不确定性和响应性之间实现具有挑战性的权衡。这对于面向保护(即P类)的pmu尤其重要。为了在不延长数据记录大小和相关延迟的情况下提高估计精度,本文提出了一种增强了初级阶段的泰勒卡尔曼滤波器(TKF),该滤波器能够在短观测间隔内白化可能出现的窄带干扰。使用动态估计器(如TKF)的动机是需要跟踪可能在智能电网中发生的电压或电流交流波形的突然幅度或相位变化。然而,尽管基本TKF对不同于白噪声的干扰非常敏感,但所提出的白化技术能够在谐波和幅值或相位阶跃变化的影响下,甚至在一个周期的观测间隔内,大大提高同步相幅值、相位、频率和频率变化率(ROCOF)的估计精度。在IEEE/IEC标准60255-118-1:2018中报告的其他P级测试条件下,性能仅略有下降。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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