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http://dx.doi.org/10.1007/s43236-022-00440-y

Wavelet packet transform and improved complete ensemble empirical mode decomposition with adaptive noise based power quality disturbance detection  

Mei, Yu (Shandong University of Technology)
Wang, Yajing (Shandong University of Technology)
Zhang, Xiangke (Shandong University of Technology)
Liu, Shiqi (Shandong University of Technology)
Wei, Qinqin (Shandong University of Technology)
Dou, Zhenhai (Shandong University of Technology)
Publication Information
Journal of Power Electronics / v.22, no.8, 2022 , pp. 1334-1346 More about this Journal
Abstract
Given the low accuracy of power quality disturbance (PQD) detection, a PQD detection method based on the wavelet packet transform (WPT) and improved complete ensemble empirical mode decomposition with adaptive noise (ICEEMDAN) is proposed in this paper. First, the wavelet packet transform is used to preprocess the signal to suppress noise interference. Then, ICEEMDAN technology is adopted to calculate the local mean value by adding adaptive noise. In addition, different intrinsic mode functions (IMFs) are obtained through residual subtraction. Furthermore, the effective IMFs are calculated by the permutation entropy method to reduce false modal components and to suppress residual noise. Finally, a Hilbert transform (HT) is performed to extract the detection signal parameters. The obtained results demonstrate that this method can improve the detection accuracy and PQD speed, which results in a strong anti-noise capability.
Keywords
Power quality disturbance; Wavelet packet transform; ICEEMDAN; Permutation entropy; Hilbert transform;
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Times Cited By KSCI : 2  (Citation Analysis)
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