基于时频分析的配电网行波故障定位研究

发布时间：2019-01-28 19:48

【摘要】：配电网作为电网中与用户直接连接的重要环节,具有对电能进行最终分配的职能,一旦配电网发生故障,将会导致短时或者长时间停电,给生产和生活带来不便。而另一方面,配电网络分支众多,人工巡线费时费力,因此快速、准确的定位故障发生地点就具有着重大的意义。本文采用行波测距法,行波测距法的关键在于行波波头的准确提取。在含噪声情况下,波头可能被噪声覆盖。传统的时频算法如短时傅里叶变换、小波变换在含噪情况下无法准确的识别行波波头。因此文章采用同步压缩小波变换及一种针对被测信号进行自动频率选择的时频分析方法,在含噪情况下,保证算法的实时性和准确性。文章首先在Matlab中搭建了多端配电线路模型,对短时傅里叶变换、小波变换、S变换以及同步压缩小波变换进行了对比。其中,S变换准确度最高但实时性较差,而同步压缩小波变换抗噪性较S变换较差。因此,文章采用自动频率选择S变换对多端配电网中的故障行波信号进行分析,结果表明在有无噪声情况下,自动频率选择S变换均能准确、快速的识别行波波头,对故障发生地点进行定位。
[Abstract]:As an important link of direct connection between distribution network and users, distribution network has the function of final distribution of electric energy. Once the distribution network fails, it will lead to short-term or long-term power outages, which will bring inconvenience to production and daily life. On the other hand, the distribution network has many branches and manual inspection takes time and effort, so it is of great significance to locate the fault location quickly and accurately. In this paper, traveling wave ranging method is used, the key of traveling wave ranging method lies in accurate extraction of traveling wave head. In the case of noise, the wave head may be covered by noise. Traditional time-frequency algorithms such as short-time Fourier transform and wavelet transform can not accurately identify the traveling wave head in the case of noise. Therefore, this paper adopts the synchronous compression wavelet transform and a time-frequency analysis method for automatic frequency selection of the measured signal, which ensures the real-time and accuracy of the algorithm in the case of noise. In this paper, a multi-terminal distribution line model is built in Matlab, and the short time Fourier transform (STFT), wavelet transform (WT), S transform and synchronous compression wavelet transform (SWT) are compared. Among them, the accuracy of S transform is the highest, but the real time is poor, and the noise resistance of synchronous compression wavelet transform is worse than that of S transform. Therefore, automatic frequency selective S transform is used to analyze the fault traveling wave signal in multi-terminal distribution network. The results show that the automatic frequency selection S transform can identify the traveling wave head accurately and quickly under the condition of noise or not. Locate the fault location.
【学位授予单位】：西安理工大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TM711

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