High-impedance ground fault identification method for distribution networks based on data-knowledge joint driving

Authors

• Ming Chen, School of Electrical & Information Engineering ， Changsha University of Science & Technology ， Changsha 410114， China;Anyang Cigarette Factory ， China Tobacco Henan Industrial Co .， Ltd.， Anyang 455000， China
• Tianle Li, School of Electrical & Information Engineering ， Changsha University of Science & Technology ， Changsha 410114， China
• Yilin Chen, School of Electrical & Information Engineering ， Changsha University of Science & Technology ， Changsha 410114， China
• Yang Li, School of Electrical & Information Engineering ， Changsha University of Science & Technology ， Changsha 410114， China
• Feng Deng, School of Electrical & Information Engineering ， Changsha University of Science & Technology ， Changsha 410114， ChinaFollow

Keywords

distribution network, panoramic characteristic, data-knowledge joint driving, Transformer, high- impedanceground fault

Abstract

When a high-impedance ground fault occurs in a distribution network, traditional knowledge-driven methods suffer from low accuracy in threshold selection, while data-driven methods have poor interpretability due to the lack of mechanism support. To address this problem, a data-knowledge joint-driven approach was proposed for identifying high-impedance ground faults in distribution networks. First, wavelet packet time-frequency entropy was used to quantitatively analyze the panoramic characteristics of high-impedance ground faults and normal disturbance conditions, thus revealing significant differences in their time-frequency distributions. Then, by qualitatively analyzing the characteristics of time-frequency energy spectrum matrices at different fault points, the knowledge-driven identification method based on the time-frequency energy spectrum matrix and the Transformer-based data-driven identification method were established. Guided by the characteristics of the time-frequency energy spectrum matrix, a data-knowledge joint-driven model based on a series mechanism was constructed. Finally, the simulation results of the IEEE 33-node system established in PSCAD simulation software show that the accuracy of the proposed method reaches 97.8%, and that it can accurately and sensitively detect a high-impedance ground fault with a resistance of 10 kΩ in a distribution network.

DOI

10.19781/j.issn.1673-9140.2026.03.009

First Page

89

Last Page

98

Recommended Citation

Chen, Ming; Li, Tianle; Chen, Yilin; Li, Yang; and Deng, Feng (2026) "High-impedance ground fault identification method for distribution networks based on data-knowledge joint driving," Journal of Electric Power Science and Technology: Vol. 41: Iss. 3, Article 9.
DOI: 10.19781/j.issn.1673-9140.2026.03.009
Available at: https://jepst.researchcommons.org/journal/vol41/iss3/9