基于小波变换的电压波动与闪变的研究分析

发布时间：2018-03-02 01:02

本文关键词： 电能质量电压波动与闪变小波变换 DFT　出处：《西安工程大学》2016年硕士论文　论文类型：学位论文

【摘要】：随着全球工业化的快速发展,对电能质量的要求也越来越高。电力电子行业的不断技术革命,给人们的生活带来了极大的便利的同时,也带来了电压波动与闪变等问题,给电力环境造成了严重污染。为此越来越多的电力科技工作者投入到电能质量研究的工作中去。文章简要阐明了电能质量的相关背景以及研究意义,对电压波动和闪变的来源、特征及其一些影响进行了必要的概述,同时针对国内外学者对电能质量中的电压波动研究的现状,提出当前科技人员常用的检测方法与理论。傅里叶变换适合应用于平稳的谐波分析,幅频特性上分析较好。而小波变换兼备时频局部化的优势,精确检测出闪变信号的开始时刻和结束时刻,解决了快速傅里叶变换(FFT)处理上的局限性弊端,因此小波变换常用于电压波动与闪变的分析。小波分析后子带普遍含有频谱折叠的问题,为了更好的处理折叠因子,本文将离散傅里叶变换(DFT)、离散傅里叶逆变换(IDFT)与塔式Mallat算法结合形成一种新的DFT—Mallat(DMallat)算法,通过与DFT计算短时闪变严重度stP的对比实验,验证了所提算法的可靠性和有效性,在一定程度上提高了检测短时闪变值的计算精度,从而表明了小波变换在电压波动与闪变分析中起到的重要作用。最后采用了BP网络来对单位瞬时闪变值时的频率和所对应频率的正弦电压波动值的关系进行拟合建模,BP网络具有很好的非线性函数逼近能力和内插特性,提高了拟合的精度。
[Abstract]:With the rapid development of global industrialization, the requirements for power quality are becoming higher and higher. The continuous technological revolution in power electronics industry has brought great convenience to people's lives, but also brought problems such as voltage fluctuation and flicker. It has caused serious pollution to electric power environment. Therefore, more and more electric power science and technology workers have put into the research work of power quality. This paper briefly expounds the relevant background and research significance of power quality, and the source of voltage fluctuation and flicker. At the same time, aiming at the current situation of domestic and foreign scholars' research on voltage fluctuation in power quality, The detection methods and theories commonly used by scientists and technicians are put forward. Fourier transform is suitable for stationary harmonic analysis, and the amplitude-frequency characteristic analysis is better. Wavelet transform has the advantages of time-frequency localization. The accurate detection of the start and end time of flicker signal solves the limitation of fast Fourier transform (FFT) processing. Therefore, wavelet transform is often used in the analysis of voltage fluctuation and flicker. In this paper, a new DFT-Mallatine DMallat algorithm is developed by combining DFT (inverse discrete Fourier transform) with the tower Mallat algorithm. The reliability and validity of the proposed algorithm are verified by a comparison experiment with DFT to calculate the short-time flicker severity stP. To some extent, the calculation accuracy of detecting short-time flicker is improved. The results show that wavelet transform plays an important role in the analysis of voltage fluctuation and flicker. Finally, BP neural network is used to fit the relationship between the frequency of unit instantaneous flicker and the sinusoidal voltage fluctuation of corresponding frequency. The modeling of BP neural network has good nonlinear function approximation ability and interpolation characteristics. The precision of fitting is improved.
【学位授予单位】：西安工程大学
【学位级别】：硕士
【学位授予年份】：2016
【分类号】：TM711;O174.2

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