A novel directional pilot protection method for EHV transmission lines based on S-transform and SVM
Abstract To address the issues of insufficient reliability and low sensitivity of traveling-wave (TW)-based protection caused by fault condition attributes, i.e., fault resistance and fault angle, this paper proposes a novel directional pilot protection method. By studying the propagation of fault TW on transmission lines, the relationship between the energy of the transient voltage components and the fault direction is established. The S-transform is employed to extract the time–frequency information of the fault transient voltage components, the direction identification criterion based on the energy difference between the reverse and forward transient voltage components is constructed. Support Vector Machine (SVM) is used to incorporate the fault angle and fault resistance into the fault characteristics. When the trained-SVM is employed for fault identification, it automatically applies different protection action values based on various fault condition attributes. The method is validated through extensive EMTP-RV fault simulations. The results indicate that the proposed method achieves 100% accuracy in fault identification and effectively eliminates the influence of fault condition attributes. Article Highlights A novel solution is proposed for the problem that traveling wave protection is difficult to apply under weak fault conditions. The difference between forward and reverse traveling wave energy during faults is investigated. The S-transform can efficiently extract traveling wave transient information.
Authors
- Zebo Huang (ORCID: https://orcid.org/0000-0003-2431-3741)
- Tong Zhang (ORCID: https://orcid.org/0000-0003-3233-2651)
- Yingcai Deng
- Zhenwei Guo (ORCID: https://orcid.org/0000-0002-5773-1491)
Institutions
- Guilin University of Electronic Technology (CN)
Publication Details
- Journal
- Discover Applied Sciences
- Published
- 2025-04-15
- DOI
- https://doi.org/10.1007/s42452-025-06752-5
- Citations
- 2
- Primary Topic
- Power Systems Fault Detection
- Type
- article
- Field-Weighted Citation Impact
- 2.43
Funders
- National Natural Science Foundation of China
- Natural Science Foundation of Guangxi Province