一种暂态电能质量检测新方法的研究

电能质量扰动带来的复杂信号调制特性,使得从电能质量监测数据中提取扰动信号特征依然面临困难。为提高噪声背景下复合电能质量扰动检测准确性,采用自适应无参经验小波变换(APEWT)对扰动信号进行模态分解,进而基于频率加权能量算子(FWEO)对单模态分量进行能量计算,同时通过解调提取用于扰动定位的瞬时频率和幅值特征量。一方面,APEWT中基于自适应频带分割的小波滤波器组输出仅包含有效模态分量,有效避免了模态混叠现象的出现；另一方面,FWEO噪声鲁棒性有效提高了强噪声背景下扰动特征提取的准确性。将算法应用到仿真及实测信号,结果显示该方法能够有效地追踪扰动信号的瞬时变化,且解调得到的瞬时频率和幅值也进一步证明了方法的可行性和有效性。

Research on a New Method for Transient Power Quality Detection

The complex signal modulation characteristics brought by power quality disturbance make it difficult to extract the disturbance signal characteristics from the power quality monitoring data. In order to improve the detection accuracy of composite power quality disturbance under noise, the Adaptive Parameterless Empirical Wavelet Transform (APEWT) is used to decompose the disturbance signal into IMFs, which are demodulated based on the Frequency-Weighted Energy Operator(FWEO) respectively, and then the instantaneous frequency and amplitude feature quantities for disturbance identification are accurately obtained. On the one hand, in APEWT the output of the orthogonal filter bank based on adaptive band segmentation only contains meaningful mode mono-component, which effectively avoids the phenomenon of mode mixing. On the other hand, FWEO noise robustness effectively improves the accuracy of disturbance feature extraction in strong noise background. Furthermore, applying the proposed algorithms to simulated and measured signals to verify performance, the results show that the method can effectively track the instantaneous change of the disturbance signal, and the instantaneous frequency and amplitude obtained by demodulation further prove the feasibility and effectiveness of the method.