Abstract
In accordance with power system operational standards, distribution networks are permitted to maintain operation for 1∼2 hours following a single-phase grounding fault. However, such faults may escalate into multi-point grounding events, posing severe threats to system security and operational stability. Thus, accurate and rapid fault localization is essential to enable field personnel to promptly isolate faulty sections and restore normal power supply. This paper proposes a novel fault identification method that integrates Extreme-point Symmetric Mode Decomposition (ESMD), Energy Relative Entropy (ERE), and a fault judgment matrix. The method first employs ESMD to extract fault-induced features from transient voltage signals. It then utilizes a strategic configuration of Feeder Terminal Units (FTUs) to segment the network and identify the fault section. Finally, a fault judgment matrix is constructed to precisely locate the fault point within the identified section. Simulation results under various fault scenarios, including Gaussian white-noise and additional impulse noise interference, demonstrate the method’s high accuracy and robustness, offering a reliable technical solution for fault diagnosis in distribution networks. © 2026 The Authors.
| Original language | English |
|---|---|
| Pages (from-to) | 8116-8127 |
| Number of pages | 12 |
| Journal | IEEE Access |
| Volume | 14 |
| Online published | 12 Jan 2026 |
| DOIs | |
| Publication status | Published - 2026 |
| Externally published | Yes |
Funding
This work was supported by the Science and Technology Project of Chongzuo under Grant Chongke 20231206.
Research Keywords
- energy relative entropy
- Extreme-point symmetric mode decomposition
- fault location
- feeder terminal unit
- symmetric differential energy operator
Publisher's Copyright Statement
- This full text is made available under CC-BY 4.0. https://creativecommons.org/licenses/by/4.0/
Fingerprint
Dive into the research topics of 'Research on Fault Section Location Method of Distribution Network Coupled With ESMD and Energy Relative Entropy'. Together they form a unique fingerprint.Cite this
- APA
- Author
- BIBTEX
- Harvard
- Standard
- RIS
- Vancouver