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Noise characteristics and fast filtering of synchronized frequency measurement in low voltage grid

机译:低压电网同步频率测量的噪声特性和快速滤波

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摘要

Power system monitoring is the basis of realizing operation safety and stability. The increasing integration of renewable energy generation along with the growing diffusion of nonlinear loads and micro-generators complicates the characteristics of low voltage grid, which leads to new requirements for the synchronized dynamic monitoring in low voltage electrical network. Unfortunately, the signal waveform in low voltage grid is polluted by heavy noises, which will influence the estimation accuracy of synchronized frequency measurement at low voltage side. Firstly, this paper summarizes the noise characteristics of synchronized frequency measurement at low voltage side, including white Gaussian noise, random impulsive noise and periodic impulsive noise. Secondly, based on the noise characteristic, median filtering and mean filtering methods are analyzed as the best choice of the fast noise filter. Thirdly, the optimal parameter of the filter is analyzed by simulation. The optimal length of filter window can be determined according to this simulation result in the condition that SNR is known. Finally, one filtering case of the frequency signal recorded by PMU Light is analyzed, which proves that the noise can be filtered effectively by the filter. It is worthy to emphasize that this fast filtering method is a good choice of measurement preprocessing for various online applications of synchronized frequency measurement in low voltage network.
机译:电力系统监控是实现运行安全性和稳定性的基础。可再生能源发电的日益集成,以及非线性负载和微型发电机的日益扩散,使低压电网的特性变得复杂,这导致了对低压电网同步动态监测的新要求。不幸的是,低压电网中的信号波形被重噪声污染,这将影响低压侧同步频率测量的估计精度。首先,本文总结了低压侧同步频率测量的噪声特性,包括白高斯噪声,随机脉冲噪声和周期性脉冲噪声。其次,根据噪声特性,分析了中值滤波和均值滤波方法作为快速噪声滤波器的最佳选择。第三,通过仿真分析滤波器的最佳参数。在SNR已知的情况下,可以根据该仿真结果确定滤波器窗口的最佳长度。最后,分析了PMU Light记录的频率信号的一种滤波情况,证明了滤波器可以有效地滤除噪声。值得强调的是,对于低压网络中同步频率测量的各种在线应用,这种快速滤波方法是测量预处理的不错选择。

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