基于小波分析的电能扰动研究

Power Quality Disturbance Detection Based on Wavelet Transform

为了有效准确地对电力系统的各种扰动源进行准确的定位,文章提出了一种基于小波分解的电能扰动在线监控理论。分别分析了小波分析的基本原理、MALLT以及小波变换模极大值理论。重点对小波降噪处理和模值极大理论在扰动检测中的应用进行了分析。该方法利用小波细节信号对信号的突变十分敏感的特点,当电网出现干扰时,电压信号必定出现异常波动,反映在小波分析上就是细节信号出现模极大值。在此基础上通过MATLAB编程对常见的几种扰动源进行了仿真分析,最后对实验数据进行了降噪和小波分解。通过实验仿真分析可以看到:小波变换理论对常见的几种扰动源能够进行很好的检测与定位,是一种可靠高效的电能扰动定位方法。

In order to accurate locate effectively all kinds of power system disturbance sources, this paper presents a decomposition of power disturbance monitoring based on the theory of wavelet. It analyzes the basic theory of wavelet analysis, MALLT and wavelet transform modulus maxima theory, focusing on the great theory analysis for the application of disturbance detection of wavelet de-noising and modulus. Methods using wavelet detail signal mutation on signal characteristics are very sensitive. When the grid disturbed, a voltage signal will appear abnormal fluctuated, and reflected in the wavelet analysis the detail signal modulus maxima. Simulation analysis based on the MATLAB programming on several common disturbance source, and the experimental data are used to denoise and wavelet decomposition. Through the simulation analysis we can get a conclusion that the theory of wavelet transform can be detected and good positioning on several common disturbance sources, and the theory of wavelet transform is a reliable and efficient power disturbance location method.