LAPSE:2023.26179
Published Article
LAPSE:2023.26179
A New Cross-Correlation Algorithm Based on Distance for Improving Localization Accuracy of Partial Discharge in Cables Lines
Xianjie Rao, Kai Zhou, Yuan Li, Guangya Zhu, Pengfei Meng
March 31, 2023
Locating the partial discharge (PD) source is one of the most effective means to locate local defects in power cable lines. The sampling rate and the frequency-dependent characteristic of phase velocity have an obvious influence on localization accuracy based on the times of arrival (TOA) evaluation algorithm. In this paper, we present a cross-correlation algorithm based on propagation distance to locate the PD source in cable lines. First, we introduce the basic principle of the cross-correlation function of propagation distance. Then we verify the proposed method through a computer simulation model and investigate the influences of propagation distance, sampling rate, and noise on localization accuracy. Finally, we perform PD location experiments on two 250 m 10 kV XLPE power cables using the oscillation wave test system. The simulation and experiment results indicate that compared with traditional TOA evaluation methods, the proposed method has superior locating precision.
Keywords
cross-correlation function, localization accuracy, partial discharge location, power cable
Suggested Citation
Rao X, Zhou K, Li Y, Zhu G, Meng P. A New Cross-Correlation Algorithm Based on Distance for Improving Localization Accuracy of Partial Discharge in Cables Lines. (2023). LAPSE:2023.26179
Author Affiliations
Rao X: College of Electrical Engineering, Sichuan University, Chengdu 610065, China
Zhou K: College of Electrical Engineering, Sichuan University, Chengdu 610065, China
Li Y: College of Electrical Engineering, Sichuan University, Chengdu 610065, China
Zhu G: College of Electrical Engineering, Sichuan University, Chengdu 610065, China
Meng P: College of Electrical Engineering, Sichuan University, Chengdu 610065, China
Journal Name
Energies
Volume
13
Issue
17
Article Number
E4549
Year
2020
Publication Date
2020-09-02
Published Version
ISSN
1996-1073
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PII: en13174549, Publication Type: Journal Article
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LAPSE:2023.26179
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doi:10.3390/en13174549
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