本文選題：暫態(tài)電能質(zhì)量 + 小波去噪��； 參考：《寧夏大學(xué)》2016年碩士論文

【摘要】：評估一種檢測方法優(yōu)劣的關(guān)鍵所在就是看這種方法能否對暫態(tài)電能質(zhì)量擾動起、止時(shí)刻進(jìn)行準(zhǔn)確、快速的定位,本文旨在對暫態(tài)電能的五類典型擾動(包括電壓驟升、電壓驟降、暫態(tài)振蕩、電壓中斷、電壓閃爍)的起、止時(shí)刻的定位分析進(jìn)行實(shí)現(xiàn)。首先通過小波包去噪法對染噪擾動信號進(jìn)行去噪處理,其次,通過希爾伯特-黃變換(Hilbert-huang Transform,簡稱HHT)對各擾動的起、止時(shí)刻進(jìn)行提取。文中包含了對小波去噪和小波包去噪兩種方法的去噪效果對比、篩選,也涵蓋了小波變換檢測法和希爾伯特-黃變換檢測法的定位效果對比,通過對比,選擇出檢測性能穩(wěn)定且準(zhǔn)確的檢測方法,并結(jié)合Matlab實(shí)現(xiàn)擾動定位的建模仿真過程。本文的主要內(nèi)容和研究成果如下：(1)本文利用小波包去噪方法和小波去噪方法分別對染噪信號進(jìn)行去噪,選取分解層數(shù)為3層、5層、7層進(jìn)行仿真,隨著分解層數(shù)的遞增,去噪效果呈現(xiàn)差-優(yōu)-差的趨勢變化,且小波包去噪的效果比小波去噪的好：兩種方法均在分解層數(shù)為5層時(shí)去噪效果達(dá)到最佳。(2)為了進(jìn)一步確定小波包去噪方法中哪類函數(shù)的去噪效果更好,我們選取db1、db3、db5、 db7、sym1、sym3、sym5、sym8八種函數(shù)進(jìn)行去噪效果對比,仿真發(fā)現(xiàn)效果較好的是db3、db5、 sym5、sym8四種函數(shù),我們又對這四類函數(shù)的去噪效果進(jìn)行了對比。綜合(1)、(2)兩點(diǎn),最終得出在分解層數(shù)為5層時(shí),sym5函數(shù)的去噪效果最好。(3)本文使用了兩種方法來對暫態(tài)電能質(zhì)量的擾動進(jìn)行定位。第一種是根據(jù)小波算法原理進(jìn)行檢測,即小波變換檢測法。第二種是根據(jù)希爾伯特-黃變換檢測算法進(jìn)行檢測,即為希爾伯特-黃變換檢測法,分別用這兩種方法檢測擾動的起、止時(shí)刻,對檢測數(shù)據(jù)進(jìn)行對比。對含噪信號進(jìn)行檢測時(shí),小波算法對電壓閃爍、暫態(tài)振蕩、電壓驟降三類擾動不能準(zhǔn)確定位,對于電壓閃爍擾動設(shè)置的四個擾動點(diǎn)直接檢測不出來,故該檢測方法在實(shí)驗(yàn)中會導(dǎo)致暫態(tài)電能質(zhì)量擾動檢測的準(zhǔn)確率下降。(4)本文使用的希爾伯特-黃變換檢測算法對電壓驟升、電壓驟降、電壓閃爍、暫態(tài)振蕩和電壓中斷這五類典型的暫態(tài)電能質(zhì)量擾動信號進(jìn)行了定位分析,從仿真結(jié)果看,這種檢測方法能夠得到擾動發(fā)生處的準(zhǔn)確數(shù)據(jù)。說明希爾伯特-黃變換檢測算法是切實(shí)可行的。并且在定位之前,先使用了小波包去噪算法對信號進(jìn)行去噪,進(jìn)一步提高了擾動檢測的準(zhǔn)確性。也為電力系統(tǒng)擾動治理提供了更加準(zhǔn)確、可靠的依據(jù)。
[Abstract]:The key to evaluate a detection method is to see if the method can accurately and quickly locate the transient power quality disturbance. This paper aims at five types of typical transient power disturbance (including voltage surge). Voltage sag, transient oscillation, voltage interruption, voltage flicker. Firstly, wavelet packet denoising method is used to Denoise the noisy disturbance signal. Secondly, Hilbert-huang transform (HHT-HHT) is used to extract the disturbance. This paper includes the comparison of the denoising effect of wavelet denoising and wavelet packet denoising, screening, and the comparison of localization effect between wavelet transform detection method and Hilbert-Huang transform detection method. The stable and accurate detection method is selected, and the modeling and simulation process of disturbance location is realized with Matlab. The main contents and research results of this paper are as follows: 1) in this paper, wavelet packet denoising method and wavelet denoising method are used to Denoise the noisy signals, and the decomposition layers are selected as three layers and five layers and seven layers for simulation. The effect of de-noising shows a trend of poor, excellent and bad. The effect of wavelet packet denoising is better than that of wavelet denoising: both of the two methods achieve the best denoising effect when the number of decomposition layers is 5 layers.) in order to further determine which function of wavelet packet denoising method is better than wavelet packet denoising method, the denoising effect of wavelet packet denoising method is better than wavelet packet denoising method. We compare the denoising effects of the eight functions, db1, db3, DB7, and db7, and we compare the denoising effects of the four functions. The results of simulation show that the four functions are better, db3ndb5 and Sym5sym8, and we also compare the denoising effects of these four functions. In this paper, two methods are used to locate the disturbance of transient power quality when the decomposed layer number is 5 layers, and the denoising effect of the sym5 function is the best. The first is based on the principle of wavelet algorithm, namely wavelet transform detection method. The second is based on Hilbert-Huang transform detection algorithm, that is, Hilbert-Huang transform detection method, using these two methods to detect the beginning and end of the disturbance, the detection data are compared. In the detection of noisy signals, the wavelet algorithm can not accurately locate three kinds of disturbances, such as voltage flicker, transient oscillation and voltage drop, but it can not directly detect the four disturbance points set by voltage scintillation disturbance. Therefore, the accuracy of transient power quality disturbance detection will be decreased in the experiment.) the Hilbert-Huang transform detection algorithm used in this paper is used to detect voltage sudden rise, voltage drop, voltage flicker. Five typical transient power quality disturbance signals, transient oscillation and voltage interruption, are located and analyzed. From the simulation results, the accurate data of the disturbance can be obtained by this method. It shows that Hilbert-Huang transform detection algorithm is feasible. Before locating, wavelet packet denoising algorithm is used to Denoise the signal, which further improves the accuracy of disturbance detection. It also provides a more accurate and reliable basis for power system disturbance control.
【學(xué)位授予單位】：寧夏大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2016
【分類號】：TM711

【參考文獻(xiàn)】

相關(guān)期刊論文 前10條

1 陳雷;鄭德忠;趙興濤;廖文U，

本文編號：2012972