| Autor: |
Zhiwei Yao, Yang Liu, Jian Chen, Jinpeng Ji, Mengdi Zhang, Yanyong Gong |
| Jazyk: |
angličtina |
| Rok vydání: |
2024 |
| Předmět: |
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| Zdroj: |
IEEE Access, Vol 12, Pp 10932-10945 (2024) |
| Druh dokumentu: |
article |
| ISSN: |
2169-3536 |
| DOI: |
10.1109/ACCESS.2024.3352258 |
| Popis: |
Aimed at the high-impedance fault detection problem, this paper proposes a fault-feature enhancement method for actively detecting high-impedance faults. The essential characteristic of this method is that the fault features are actively enhanced without affecting the normal terminal voltage. The method consists of two stages, i.e., the feature-enhancement stage and the fault-detection stage. The terminal voltage difference between the fault and normal state is analyzed in the first stage. Then, the feasibility of enhancing terminal voltage difference by the auxiliary signal is proved, and the selection criteria of the auxiliary signal is determined based on IEEE standards. In the second stage, the local-scale energy entropy ratios are applied to reconstruct the measurements. Then, high-impedance faults are detected by discriminating reconstructed data statistical characteristics differences before and during the fault. The simulation results show that the proposed method can accurately identify high-impedance faults with 75 $\text{k}{\Omega }$ transition impedance in an environment with a signal-to-noise ratio of 15 dB and reliably detect the faults with 75 $\text{k}{\Omega }$ transition impedance on buses and feeders at different positions. The method is robust to noise, transition impedance, and switching events. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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