Open Access

ARTICLE

Study of Denoising in the Electricity Anti-Stealing Detection Based on VMD-WTD Combination

Huakun Que¹, Guolong Lin², Wenchong Guo¹, Xiaofeng Feng¹, Zetao Jiang¹, Yunfei Cao^2,*, Jinmin Fan², Zhixian Ni³

1 Metrology Center of Guangdong Power Grid Corporation, Shenzhen, 518049, China
2 School of Automation, Guangdong University of Technology, Guangzhou, 510006, China
3 China-EU School of Clean and Renewable Energy, Huazhong University of Science and Technology, Wuhan, 430074, China

* Corresponding Author: Yunfei Cao. Email:

Energy Engineering 2022, 119(4), 1453-1466. https://doi.org/10.32604/ee.2022.018448

Received 25 July 2021; Accepted 17 September 2021; Issue published 23 May 2022

Abstract

In order to solve the failure of electricity anti-stealing detection device triggered by the noise mixed in high-frequency electricity stealing signals, a denoising method based on variational mode decomposition (VMD) and wavelet threshold denoising (WTD) was applied to extract the effective high-frequency electricity stealing signals. First, the signal polluted by noise was pre-decomposed using the VMD algorithm, the instantaneous frequency means of each pre-decomposed components was analyzed, so as to determine the optimal K value. The optimal K value was used to decompose the polluted signal into K intrinsic mode components, and the sensitive mode components were determined through the cross-correlation function. Next, each sensitive mode was reconstructed. Finally, the reconstructed signal denoised using the wavelet threshold to obtain the denoised signal. The simulation analysis and experimental results show that the proposed method is superior to the traditional VMD method, FFT method and EMD method, as it can effectively eliminate the noise and enhance the reliability of high-frequency electricity stealing signal detection.

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