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Dynamic phasor and frequency estimator for phasor measurement units

机译:用于相量测量单元的动态相量和频率估计器

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摘要

Synchrophasors and frequency estimations play an increasingly important role in power systems. Discrete Fourier transform (DFT) may introduce errors into phasor and frequency estimations under dynamic conditions, such as power oscillation. A dynamic phasor and frequency estimator for phasor measurement units (PMUs) is proposed to improve accuracy by considering dynamic characteristics of power systems expressed as Taylor derivatives. Firstly, phasor estimations of sequence components of diffident data windows are attained via DFT. Secondly Taylor derivatives, expressed by adjacent phasors at different data windows, are employed to improve accuracy of estimations by reassigning estimations with the knowledge of dynamic characteristics. Finally, dynamic characteristics of positive sequence components are applied to estimate the fundamental frequency with less delay compared to a state-of-the-art algorithm, phasor-based synchronised frequency measurement (PSFM). To verify the performance, a set of digital dynamic tests and a power oscillation model using PSCAD/EMTDC are presented. The simulation results show that proposed algorithm can achieve highly accurate estimations of phasor and frequency over a wide range of dynamic conditions. Even though a minor increase in calculation burden is required, this technique provides accurate phasor and frequency estimations without changing the legacy structure of PMU devices. Additionally, it has been found that proposed algorithm really meets the needs of online applications.
机译:同步相量和频率估计在电力系统中起着越来越重要的作用。离散傅里叶变换(DFT)可能在动态条件下(例如功率振荡)将误差引入相量和频率估计中。提出了一种用于相量测量单元(PMU)的动态相量和频率估计器,以通过考虑表示为泰勒导数的电力系统的动态特性来提高精度。首先,通过DFT获得不同数据窗口的序列分量的相量估计。其次,由相邻相量在不同数据窗口表示的泰勒导数用于通过重新分配具有动态特征知识的估计来提高估计的准确性。最后,与最新算法,基于相量的同步频率测量(PSFM)相比,正序分量的动态特性可用于以更低的延迟估算基本频率。为了验证性能,提出了一组数字动态测试和使用PSCAD / EMTDC的功率振荡模型。仿真结果表明,所提出的算法可以在较宽的动态条件下实现对相量和频率的高精度估计。即使需要稍微增加计算负担,该技术也可以提供准确的相量和频率估计,而无需更改PMU设备的传统结构。另外,已经发现所提出的算法确实满足在线应用的需求。

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