【摘要】：配電網(wǎng)作為電網(wǎng)中與用戶直接連接的重要環(huán)節(jié),具有對(duì)電能進(jìn)行最終分配的職能,一旦配電網(wǎng)發(fā)生故障,將會(huì)導(dǎo)致短時(shí)或者長時(shí)間停電,給生產(chǎn)和生活帶來不便。而另一方面,配電網(wǎng)絡(luò)分支眾多,人工巡線費(fèi)時(shí)費(fèi)力,因此快速、準(zhǔn)確的定位故障發(fā)生地點(diǎn)就具有著重大的意義。本文采用行波測距法,行波測距法的關(guān)鍵在于行波波頭的準(zhǔn)確提取。在含噪聲情況下,波頭可能被噪聲覆蓋。傳統(tǒng)的時(shí)頻算法如短時(shí)傅里葉變換、小波變換在含噪情況下無法準(zhǔn)確的識(shí)別行波波頭。因此文章采用同步壓縮小波變換及一種針對(duì)被測信號(hào)進(jìn)行自動(dòng)頻率選擇的時(shí)頻分析方法,在含噪情況下,保證算法的實(shí)時(shí)性和準(zhǔn)確性。文章首先在Matlab中搭建了多端配電線路模型,對(duì)短時(shí)傅里葉變換、小波變換、S變換以及同步壓縮小波變換進(jìn)行了對(duì)比。其中,S變換準(zhǔn)確度最高但實(shí)時(shí)性較差,而同步壓縮小波變換抗噪性較S變換較差。因此,文章采用自動(dòng)頻率選擇S變換對(duì)多端配電網(wǎng)中的故障行波信號(hào)進(jìn)行分析,結(jié)果表明在有無噪聲情況下,自動(dòng)頻率選擇S變換均能準(zhǔn)確、快速的識(shí)別行波波頭,對(duì)故障發(fā)生地點(diǎn)進(jìn)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.
【學(xué)位授予單位】：西安理工大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：TM711

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本文編號(hào)：2417261