基于小波域相子的电压暂降特征提取与成因辨识

有效提取电压暂降的特征并进行成因辨识是确定治理方案的前提。在多分辨分析基础上发展起来的离散小波变换(DWT)具有简单、快速和信息非冗余等特点，但一般认为不易于提取电压暂降信号的相位跳变特征。基于小波域相子方法对电压暂降的幅值和相角特征进行了有效提取。通过小波域相子的幅值和相位信息构造出电压暂降成因辨识特征指标。最后采用支持向量机(SVM)方法进行了电压暂降成因的辨识。结果表明，所提方法可以有效实现电压暂降的特征提取和成因辨识。

Wavelet-based phasor to detect and identify the voltage sag characteristics

Characteristics extraction and classification of voltage sags is the precondition for choosing the right power quality management measures. Based on the multi-resolution analysis, the Discrete Wavelet Transform (DWT) is simple, fast and non-redundant, but it is generally considered that it is difficult for the wavelet transform to detect the phase shift of the voltage sag. Based on the wavelet-based phasor method, this paper detects and identifies the amplitude and phasor characteristics of voltage sag. Then the source identification features of voltage sag according to amplitude and phasor information of wavelet-based phasor are constructed. Finally, the cause identification of voltage sag is carried out by using the Support Vector Machine (SVM) method. The results show that the proposed method can realize the characteristics extraction and cause identificatin of voltage sag effectively. This work is supported by National Natural Science Foundation of China (No. 51577115).