Explainable Deep Learning Approach for High Impedance Fault Localization in Resonant Distribution Networks Considering Quantization Noise

Gao, Jian-Hong; Guo, Mou-Fa; Lin, Shuyue; Hong, Qiteng

Abstract

In addressing the quantization noise challenge in high impedance fault (HIF) localization within resonant distribution networks, we propose a cutting-edge, explainable deep learning approach that significantly advances existing methods. This approach utilizes differential zero-sequence voltage (DZSV) and zero-sequence current (ZSC) and introduces a novel “Vague” classification to improve localization accuracy by effectively managing quantization noise-distorted signals. This approach extends beyond the conventional binary classification of “Fault” and “Sound,” incorporating a multi-scale feature attention (MFA) mechanism for enriched internal explainability and applying gradient-weighted class activation mapping (Grad-CAM) to visualize critical input areas precisely. Our model, validated in an industrial prototype, exhibits unparalleled adaptability across various environmental conditions, including environmental noise, variable sampling rates, and triggering deviations. Comparative analysis reveals that our approach outperforms existing methods in managing diverse fault scenarios.

Citation

Gao, J.-H., Guo, M.-F., Lin, S., & Hong, Q. (online). Explainable Deep Learning Approach for High Impedance Fault Localization in Resonant Distribution Networks Considering Quantization Noise. International Journal of Circuit Theory and Applications, https://doi.org/10.1002/cta.4260

• Journal Article Type: Article
• Acceptance Date: Aug 11, 2024
• Online Publication Date: Sep 15, 2024
• Deposit Date: Aug 14, 2024
• Publicly Available Date: Sep 16, 2025
• Journal: International Journal of Circuit Theory and Applications
• Print ISSN: 0098-9886
• Electronic ISSN: 1097-007X
• Publisher: John Wiley and Sons
• Peer Reviewed: Peer Reviewed
• DOI: https://doi.org/10.1002/cta.4260
• Keywords: Explainable deep learning; Fault localization; High impedance fault; Quantization noise; Resonant distribution networks
• Public URL: https://hull-repository.worktribe.com/output/4788215