Unified Faulty Feeder Detection Criteria and High-Speed Protection Scheme for High Impedance Faults in Resonant Grounding MV Networks
The identification of high impedance fault (HIF) is of significant importance for the safe operation of resonant ground-ing medium voltage (MV) networks. Current protection methods struggle to reliably detect these types of faults, necessitating the urgent development of an effective HIF detection technique. Starting from the differential equation solution of the HIF equiva-lent circuit, this paper discusses in detail the evolution of the am-plitude and polarity characteristics of the zero-sequence current during the transient and steady-state periods after a fault. It demonstrates that the zero-sequence current shares a common evolution process under over damped and under damped fault conditions, leading to the establishment of the unified faulty feeder detection criteria. Upon this discoveries, a novel high-speed pro-tection scheme is introduced. The method, which constructs a pair of mutually orthogonal reference vectors in high-dimensional space, enables independent processing of zero-sequence current signals at each measurement point. This effectively reduces data transmission volume and accelerating detection speed. To validate the accuracy and extensive applicability of the proposed method-ology, different fault conditions was conducted both on an active distribution network model and in the field environment. In all instances, HIF characteristics were reliably identified.
Authors
- Guoqiang Sun (ORCID: https://orcid.org/0000-0002-2368-5343)
- Zhinong Wei (ORCID: https://orcid.org/0000-0002-8277-7336)
- Haixiang Zang
- Sheng Chen (ORCID: https://orcid.org/0000-0002-9283-4197)
- Zhihua Yin (ORCID: https://orcid.org/0000-0003-1250-302X)
Institutions
- Hohai University (CN)
- Changzhou Institute of Technology (CN)
Publication Details
- Journal
- IEEE Transactions on Smart Grid
- Published
- 2025-06-16
- DOI
- https://doi.org/10.1109/tsg.2025.3579803
- Citations
- 3
- Primary Topic
- Power Systems Fault Detection
- Type
- article
- Field-Weighted Citation Impact
- 3.64
Funders
- National Natural Science Foundation of China