A Novel Method to Detect High Impedance Fault in Electric Vehicle Integrated Distribution System
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Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-53717-2_24
Reference14 articles.
1. Joga, S.R.K., Sinha, P., Maharana, M.K., Jena, C.: Tunable Q-wavelet transform based entropy measurement to detect and classify faults in certs microgrid test bed. In: 2021 International Conference in Advances in Power, Signal, and Information Technology (APSIT), pp. 1–6 (2021). https://doi.org/10.1109/APSIT52773.2021.9641113
2. Joga, S.R.K., Sinha, P., Maharana, M.K.: A novel graph search and machine learning method to detect and locate high impedance fault zone in distribution system. Eng. Rep. 5(1), e12556 (2023). https://doi.org/10.1002/eng2.12556
3. Gomes, D.P.S., Ozansoy, C.: VeHIF: an accessible vegetation high-impedance fault data set format. IEEE Trans. Power Delivery 37(6), 5473–5475 (2022). https://doi.org/10.1109/TPWRD.2022.3195002
4. Guillen, D., Olveres, J., Torres-García, V., Escalante-Ramírez, B.: Hermite transform based algorithm for detection and classification of high-impedance faults. IEEE Access 10, 79962–79973 (2022). https://doi.org/10.1109/ACCESS.2022.3194525
5. Ghaderi, A., Ginn, H.L., III., Mohammadpour, H.A.: High impedance fault detection: a review. Electr. Power Syst. Res. 143, 376–388 (2017)
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