A Critical Analysis on Different High Impedance Fault Detection Schemes

References

• M. Wei, W. Liu, H. Zhang, F. Shi and W. Chen, “Distortion-based detection of high impedance fault in distribution systems,” IEEE Trans. Power Delivery, vol. 36, no. 3, pp. 1603–1618, 2021. DOI: 10.1109/TPWRD.2020.3011930.
   Web of Science ®Google Scholar
• M. H. Hilman, M. A. Rodriguez and R. Buyya, “Multiple workflows scheduling in multi-tenant distributed systems: a taxonomy and future directions,” ACM Comput. Surv., vol. 53, no. 1, pp. 1–39, 2021. DOI: 10.1145/3368036.
   Web of Science ®Google Scholar
• B. Mclnerney, “Who is Responsible for Tree Limbs on Power Lines”, https://www.gotreequotes.com, 10 August 2023.
   Google Scholar
• C. Brightwell, “Power Pole Electrical Fire (Arcing and Flashing)”, lOQEBqdCQeM, www.YouTube.com, 6 Feb 2016.
   Google Scholar
• J. Vico, M. Damiak, C. Wester and A. Kulshrestha, “High impedance fault detection on rural electric distribution systems,” IEEE Rural Electric Power Conference (REPC), 2010. pp. B3–B3, 16–19 May Orlando, Florida, USA.
   Google Scholar
• H. Wu, Impedance Fault Characteristics and Detection Methods." PhD dissertation, "Study of High. UNSW Sydney, 2015.
   Google Scholar
• J. J. Theron, A. Pal and A. Varghese, “Tutorial on high impedance fault detection,” 71st Annual Conference for Protective Relay Engineers (CPRE), IEEE: College Station, Texas, USA, 2018, pp. 1–23.
   Google Scholar
• B. M. Aucoin and R. H. Jones, “High impedance fault detection implementation issues,” IEEE Trans. Power Delivery, vol. 11, no. 1, pp. 139–148, 1996. DOI: 10.1109/61.484010.
   Web of Science ®Google Scholar
• Q. M. Xiao, M. F. Guo and D. Y. Chen, “High-impedance fault detection method based on one-dimensional variational prototyping-encoder for distribution networks,” IEEE Syst. J., vol. 16, no. 1, pp. 966–976, 2022. DOI: 10.1109/JSYST.2021.3053769.
   Web of Science ®Google Scholar
• F. Hojatpanah, F. B. Ajaei and H. Tiwari, “Reliable detection of high-impedance faults using mathematical morphology,” Electric Power Syst. Res., vol. 216, pp. 109078, 2023. DOI: 10.1016/j.epsr.2022.109078.
   Web of Science ®Google Scholar
• J. Doria-Garcia, C. Orozco-Henao, L. U. Iurinic and J. D. Pulgarín-Rivera, “High impedance fault location: generalized extension for ground faults,” Int. J. Elect. Power Energy Syst., vol. 114, pp. 105387, 2020. DOI: 10.1016/j.ijepes.2019.105387.
   Web of Science ®Google Scholar
• M. Aucoin, “Status of high impedance fault detection,” IEEE Trans. Power App. Syst., vol. PAS-104, no. 3, pp. 637–644, 1985. DOI: 10.1109/TPAS.1985.318999.
   Web of Science ®Google Scholar
• C. G. Wester, “High impedance fault detection on distribution systems,” 42nd Annual Rural Electric Power. IEEE: Kanpur, India, 26–28 April, 1998, pp. c5–1.
   Google Scholar
• M. Adamiak, Mark, C.,   Wester, M. Thakur and C. Jensen, “High impedance fault detection on distribution feeders,” GE Ind. Sol., pp. 2–11, 2006.
   Google Scholar
• M. Sedighizadeh, A. Rezazadeh and N. I. Elkalashy, “Approaches in high impedance fault detection a chronological review,” AECE, vol. 10, no. 3, pp. 114–128, 2010. DOI: 10.4316/aece.2010.03019.
   Google Scholar
• J. L. Willis, H. J. Renninger, D. K. Schnake and H. D. Alexander, “Xerophytic hardwood retention promotes competition over facilitation in longleaf pine woodlands in the absence of fire,” Forest Ecology Manage., vol. 531, pp. 120792, 2023. DOI: 10.1016/j.foreco.2023.120792.
   Web of Science ®Google Scholar
• S. T. Yousif and R. M. Najem, “Material price enfluence on the optimum design of different structural members,” Amer. J. Civil Engng., vol. 5, no. 6, pp. 331–338, 2017.
   Google Scholar
• S. A. Jabbar and S. B. Farid, “Replacement of steel rebars by GFRP rebars in the concrete structures,” Karbala Int. J. modern Sci., vol. 4, no. 2, pp. 216–227, 2018. DOI: 10.1016/j.kijoms.2018.02.002.
   Google Scholar
• A. Bhatraj, P. K. Srivastava, S. Biswas and P. K. Nayak, “High Impedance Fault Detection in Microgrids Using Cross-Alienation Coefficient,” Fifth International Conference on Microelectronics, Computing and Communication Systems (MCCS). Ranchi, India, July 11–12, 2020, pp. 41–54.
   Google Scholar
• C. L. Huang, H. Y. Chu, and Ming-Tong Chen, “Algorithm comparison for high impedance fault detection based on staged fault test”, IEEE Trans. Power Delivery., vol. 3, no. 4, pp. 1427–1435, 1988. DOI: 10.1109/61.193941.
   Web of Science ®Google Scholar
• B. D. Russell, “Computer relaying and expert systems: new tools for detecting high impedance faults,” Electric Power Syst. Res., vol. 20, no. 1, pp. 31–37, 1990.
   Web of Science ®Google Scholar
• J. T. Tengdin, et al., “Application of high impedance fault detectors: a summary of the panel session held at the 1995 IEEE PES summer meeting,” Transmission and Distribution Conference and Exposition, LA, USA, 1996, pp. 116–122.
   Google Scholar
• H. S. Choi, S. H. Kang, C. H. Kim, M. C. Shin, W. G. Jung and B. K. Lee, “A study on the high impedance fault detection using neural networks,” Trans. Korean Inst. Elect. Eng., vol. 47, pp. 875–879, 1998.
   Google Scholar
• M. Mishra and R. R. Panigrahi, “Taxonomy of high impedance fault detection algorithm,” Measurement, vol. 148, pp. 106955, 2019. DOI: 10.1016/j.measurement.2019.106955.
   Web of Science ®Google Scholar
• A. Ghaderi, H. L. Ginn, III and H. A. Mohammadpour, “High impedance fault detection: a review,” Electric Power Syst. Res., vol. 143, pp. 376–388, 2017. DOI: 10.1016/j.epsr.2016.10.021.
   Web of Science ®Google Scholar
• J. Gao, X. Wang, X. Wang, A. Yang, H. Yuan and X. Wei, “A high-impedance fault detection method for distribution systems based on empirical wavelet transform and differential faulty energy,” IEEE Trans. Smart Grid, vol. 13, no. 2, pp. 900–912, 2022. DOI: 10.1109/TSG.2021.3129315.
   Web of Science ®Google Scholar
• H. Ungrad, W. Winkler and A. Wiszniewski, 2020, Protection Techniques in Electrical Energy Systems. Boca Raton: CRC Press.
   Google Scholar
• A. Ghaderi, H. A. Mohammadpour, H. L. Ginn and Y. J. Shin, “High-impedance fault detection in the distribution network using the time-frequency-based algorithm,” IEEE Trans. Power Delivery, vol. 30, no. 3, pp. 1260–1268, 2015. DOI: 10.1109/TPWRD.2014.2361207.
   Web of Science ®Google Scholar
• H. Bai, B. Tang, T. Cheng and H. Liu, “High impedance fault detection method in distribution network based on improved Emanuel model and DenseNet,” Energy Report., vol. 8, pp. 982–987, 2022. DOI: 10.1016/j.egyr.2022.05.199.
   Web of Science ®Google Scholar
• X. Zeng, W. Gao and G. Yang, “High impedance fault detection in distribution network based on S-transform and average singular entropy,” Global Energy Interconnect., vol. 6, no. 1, pp. 64–80, 2023. DOI: 10.1016/j.gloei.2023.02.006.
   Google Scholar
• V. Gogula and B. Edward, “Fault detection in a distribution network using a combination of a discrete wavelet transform and a neural Network’s radial basis function algorithm to detect high-impedance faults,” Front. Energy Res., vol. 11, pp. 1101049, 2023. DOI: 10.3389/fenrg.2023.1101049.
   Web of Science ®Google Scholar
• I. Abasi-Obot, G. Shehu, A. Kunya and Y. Jibril, “High Impedance Fault Modelling and Simulation of 33kV/11kV Distribution Network Using MATLAB,” 2022 IEEE Nigeria 4th International Conference on Disruptive Technologies for Sustainable Development (NIGERCON), April, 2022. pp. 1–4. IEEE. DOI: 10.1109/NIGERCON54645.2022.9803104.
   Google Scholar
• P. Sinha, et al., “Cross‐country high impedance fault diagnosis scheme for unbalanced distribution network employing detrended cross‐correlation,” IET Generation Trans Dist., 2023. DOI: 10.1049/gtd2.12911.
   Web of Science ®Google Scholar
• E. Hamatwi, O. Imoru, M. M. Kanime and H. S. A. Kanelombe, “Comparative analysis of high impedance fault detection techniques on distribution networks,” IEEE Access, vol. 11, pp. 25817–25834, 2023. DOI: 10.1109/ACCESS.2023.3254923.
   Web of Science ®Google Scholar
• P. Varghese, M. S. P. Subathra, S. T. George, N. M. Kumar, E. S. Suviseshamuthu and S. Deb, “Application of signal processing techniques and intelligent classifiers for high-impedance fault detection in ensuring the reliable operation of power distribution systems,” Front. Energy Res., vol. 11, pp. 1114230, 2023. DOI: 10.3389/fenrg.2023.1114230.
   Web of Science ®Google Scholar
• M. Mishra, P. Routray and P. K. Rout, “A universal high impedance fault detection technique for distribution system using S-transform and pattern recognition,” Technol Econ Smart Grids Sustain Energy, vol. 1, no. 1, pp. 1–14, 2016. DOI: 10.1007/s40866-016-0011-4.
   Google Scholar
• S. Bhatta, R. Fu and Y. Zhang, “A new method of detecting and interrupting high impedance faults by specifying the Z-source breaker in DC power networks,” Electronics, vol. 9, no. 10, pp. 1654, 2020. DOI: 10.3390/electronics9101654.
   Web of Science ®Google Scholar
• A. Aljohani and I. Habiballah, “High-impedance fault diagnosis: a review,” Energies, vol. 13, no. 23, pp. 6447, 2020. DOI: 10.3390/en13236447.
   Web of Science ®Google Scholar
• L. Yao, Z. Fang, Y. Xiao, J. Hou and Z. Fu, “An intelligent fault diagnosis method for lithium battery systems based on grid search support vector machine,” Energy, vol. 214, pp. 118866, 2021. DOI: 10.1016/j.energy.2020.118866.
   Web of Science ®Google Scholar
• F. Mumtaz, et al., “High impedance faults detection and classification in renewable energy-based distribution networks using time-varying Kalman filtering technique,” Engineering Proc., vol. 20, no. 1, pp. 34, 2022.
   Google Scholar
• J. V. de Souza, G. N. Lopes, J. C. M. Vieira and E. N. Asada, “High impedance fault detection in distribution systems: an approach based on Fourier transform and artificial neural networks,” In 2020 Workshop on Communication Networks and Power Systems (WCNPS), November, 2020. pp. 1–6. IEEE. DOI: 10.1109/WCNPS50723.2020.9263766.
   Google Scholar
• I. Baqui, I. Zamora, J. Mazón and G. Buigues, “High impedance fault detection methodology using wavelet transform and artificial neural networks,” Electric Power Syst. Res., vol. 81, no. 7, pp. 1325–1333, 2011. DOI: 10.1016/j.epsr.2011.01.022.
   Web of Science ®Google Scholar
• B. Vahidi, N. Ghaffarzadeh, S. H. Hosseinian and S. M. Ahadi, “An approach to detection of high impedance fault using discrete wavelet transform and artificial neural networks,” Simulation, vol. 86, no. 4, pp. 203–215, 2010. DOI: 10.1177/0037549709340823.
   Google Scholar
• S. J. Huang and C. T. Hsieh, “High-impedance fault detection utilizing a Morlet wavelet transform approach,” IEEE Trans. Power Delivery, vol. 14, no. 4, pp. 1401–1410, 1999.
   Web of Science ®Google Scholar
• T. Biswal and S. K. Parida, “High impedance fault detection in microgrid system using Discrete wavelet transform and Support vector machine,” 2022 Second International Conference on Power, Control and Computing Technologies (ICPC2T), March, 2022. pp. 1–6. IEEE. DOI: 10.1109/ICPC2T53885.2022.9777069.
   Google Scholar
• T. Biswal, S. K. Parida and S. Mishra, “A combined approach of empirical wavelet transform and artificial neural network based high impedance fault classification in micro-grid system,” 2022 IEEE Region 10 Symposium (TENSYMP, July, 2022. pp. 1–6. IEEE. DOI: 10.1109/TENSYMP54529.2022.9864362.
   Google Scholar
• M. Y. Suliman and M. T. Alkhayyat, “High impedance fault detection in radial distribution network using discrete wavelet transform technique,” Archives Elect. Engng., pp. 873–886, 2021.
   Web of Science ®Google Scholar
• M. F. H. Bhuiya, R. Hamdan, D. M. Soomro, A. O. Idris and H. Sharif, “High impedance fault detection in 11 kV overhead line with discrete wavelet transform and independent component analysis,” IJEECS, vol. 24, no. 2, pp. 661–672, 2021. DOI: 10.11591/ijeecs.v24.i2.pp661-672.
   Google Scholar
• E. M. Lima, N. S. D. Brito and B. A. de Souza, “High impedance fault detection based on Stockwell transform and third harmonic current phase angle,” Electric Power Syst. Res., vol. 175, pp. 105931, 2019. DOI: 10.1016/j.epsr.2019.105931.
   Web of Science ®Google Scholar
• G. N. Lopes, T. S. Menezes and J. C. M. Vieira, “Harmonic selection-based analysis for high impedance fault location using Stockwell transform and random forest,” 2022 20th International Conference on Harmonics & Quality of Power (ICHQP), May, 2022. pp. 1–6. IEEE. DOI: 10.1109/ICHQP53011.2022.9808661.
   Google Scholar
• Z. H. Khorashadi, “An ANN-based high impedance fault detection scheme: design and implementation,” Int. J. Emerging Electric Power Syst., vol. 4, no. 2 2005.
   Google Scholar
• S. Roy and S. Debnath, “PSD based high impedance fault detection and classification in distribution system,” Measurement, vol. 169, pp. 108366, 2021. DOI: 10.1016/j.measurement.2020.108366.
   Web of Science ®Google Scholar
• G. Asghari, P. Pourghasem and H. Seyedi, “High impedance fault protection scheme for smart grids based on WPT and ELM considering evolving and cross-country faults,” Int. J. Elect. Power Energy Syst., vol. 107, pp. 412–421, 2019. DOI: 10.1016/j.ijepes.2018.12.019.
   Web of Science ®Google Scholar
• T. Biswal and S. K. Parida, “A novel high impedance fault detection in the micro-grid system by the summation of accumulated difference of residual voltage method and fault event classification using discrete wavelet transforms and a decision tree approach,” Electric Power Syst. Res., vol. 209, pp. 108042, 2022. DOI: 10.1016/j.epsr.2022.108042.
   Web of Science ®Google Scholar
• M. Biswal, S. Ghore, O. P. Malik and R. C. Bansal, “Development of time-frequency based approach to detect high impedance fault in an inverter interfaced distribution system,” IEEE Trans. Power Delivery, vol. 36, no. 6, pp. 3825–3833, 2021. DOI: 10.1109/TPWRD.2021.3049572.
   Web of Science ®Google Scholar
• P. V. Dhawas, P. P. Bedekar and P. V. Nandankar, “Review on High-Impedance Fault Detection Techniques,” J. The Institution Engineers (India): series, vol. C, pp. 1–13, 2023.
   Google Scholar
• E. Baharozu, S. Ilhan and G. Soykan, “High impedance fault localization: a comprehensive review,” Electric Power Syst. Res., vol. 214, pp. 108892, 2023. DOI: 10.1016/j.epsr.2022.108892.
   Web of Science ®Google Scholar
• P. V. Dhawas, P. P. Bedekar and P. V. Nandankar, “Review on high-impedance fault detection techniques,” J. Inst. Eng. India Ser. C, pp. 1–13, 2023. DOI: 10.1007/s40032-023-00932-1.
   Google Scholar
• G. N. Lopes, T. S. Menezes, D. P. Gomes and J. C. M. Vieira, “High impedance fault location methods: review and harmonic selection-based analysis,” IEEE Open J. Power Energy, vol. 10, pp. 438–449, 2023. DOI: 10.1109/OAJPE.2023.3244341.
   Google Scholar
• M. F. Guo, W. L. Liu, J. H. Gao and D. Y. Chen, “A data-enhanced high impedance fault detection method under imbalanced sample scenarios in distribution networks,” IEEE Trans. Ind. Appl., pp. 1–14, 2023. DOI: 10.1109/TIA.2023.3256975.
   Google Scholar
• L. Cui, Y. Liu, L. Wang, J. Chen and X. Zhang, “High-impedance fault detection method based on sparse data divergence discrimination in distribution networks,” Electric Power Syst. Res., vol. 223, pp. 109514, 2023. DOI: 10.1016/j.epsr.2023.109514.
   Web of Science ®Google Scholar
• K. Dubey and P. Jena, “A novel high impedance fault detection technique in smart active distribution systems,” IEEE Trans. Ind. Electron, pp. 1–11, 2023. DOI: 10.1109/TIE.2023.3285975.
   Google Scholar
• B. K. Sangeeth and V. Vinod, “High impedance fault detection using multi-domain feature with artificial neural network,” Electric Power Components Syst., vol. 51, no. 4, pp. 366–379, 2023. DOI: 10.1080/15325008.2023.2172091.
   Web of Science ®Google Scholar
• V. F. Couto and M. Moreto, “High impedance fault detection on microgrids considering the impact of VSC based generation,” IEEE Access, vol. 11, pp. 89550–89560, 2023. DOI: 10.1109/ACCESS.2023.3305958.
   Web of Science ®Google Scholar
• M. F. Guo, Z. Y. Guo, J. H. Gao and D. Y. Chen, “High-impedance fault detection methodology using time–frequency spectrum and transfer convolutional neural network in distribution networks,” IEEE Syst. J., vol. 17, no. 3, pp. 4002–4013, 2023. DOI: 10.1109/JSYST.2023.3281826.
   Web of Science ®Google Scholar
• A. Chandra, G. K. Singh and V. Pant, “A novel high impedance fault detection strategy for microgrid based on differential energy signal of current signatures and entropy estimation,” Electric Power Components Syst., pp. 1–23, 2023. DOI: 10.1080/15325008.2023.2227193.
   Web of Science ®Google Scholar
• N. Bayati and M. Savaghebi, “A high-impedance fault detection scheme for DC aircrafts based on comb filter and second derivative of voltage,” Green Energy Intelligent Transport., vol. 2, no. 2, pp. 100073, 2023. DOI: 10.1016/j.geits.2023.100073.
   Google Scholar
• C. R. Ozansoy and A. Zayegh, “Optimal sampling requirements for robust and fast vegetation high impedance fault detection,” IEEE Access, vol. 11, pp. 42924–42936, 2023. DOI: 10.1109/ACCESS.2023.3270928.
   Web of Science ®Google Scholar
• M. N. Allawi, A. N. Hussain and M. K. Wali, “High impedance fault detection in distribution feeder based on frequency spectrum and ANN,” In 2023 IEEE Jordan International Joint Conference on Electrical Engineering and Information Technology (JEEIT), IEEE, 2023, pp. 140–145. DOI: 10.1109/JEEIT58638.2023.10185852.
   Google Scholar
• Y. Liu, M. Razeghi-Jahromi and J. Stoupis, 2023. Unsupervised High Impedance Fault Detection Using Autoencoder and Principal Component Analysis. arXiv preprint arXiv:2301.01867
   Google Scholar
• Z. Moravej and M. Ghahremani, 2023, “High impedance fault detection and classification based on pattern recognition,” in Modernization of Electric Power Systems: Energy Efficiency and Power Quality, pp. 487–512. Cham: springer International Publishing.
   Google Scholar
• J. H. Gao, M. F. Guo, S. Lin and D. Y. Chen, “Application of semantic segmentation in high-impedance fault diagnosis combined signal envelope and Hilbert marginal spectrum for resonant distribution networks,” Expert Syst. Appl., vol. 231, pp. 120631, 2023. DOI: 10.1016/j.eswa.2023.120631.
   Web of Science ®Google Scholar
• A. Cooper, A. Bretas, S. Meyn and N. G. Bretas, “High impedance fault detection through quasi-static state estimation: a parameter error modeling approach,” 2023 IEEE Power & Energy Society Innovative Smart Grid Technologies Conference (ISGT), 2023. January. pp. 1–5. IEEE. DOI: 10.1109/ISGT51731.2023.10066369.
   Google Scholar
• H. Abniki, M. Hajati Samsi, B. Taheri and S. A. Hosseini, “High impedance fault detection in power transmission lines using Hilbert transform and instantaneous frequency,” Int. J. Ind. Electronics Control Optimization, vol. 6, no. 1, pp. 1–11, 2023.
   Google Scholar
• M. Bhatnagar, A. Yadav and A. Swetapadma, “High Impedance Fault Detection in Distribution Networks using Unsupervised Learning Technique,” In 2023 2nd International Conference for Innovation in Technology (INOCON), March, 2023, pp. 1–6. IEEE. DOI: 10.1109/INOCON57975.2023.10101324.
   Google Scholar
• L. Solankee, A. Rai and M. Kirar, “High impedance fault detection in microgrid to enhance resiliency against PMU outage,” Int. J. Computing Digital Syst., vol. 14, no. 1, pp. 1–xx, 2023.
   Google Scholar
• S. M. Nobakhti and A. Ketabi, “A protection scheme based on impedance for LV and MV lines in microgrids with high-impedance fault detection capability,” Front. Energy Res., vol. 11, pp. 1125861, 2023. DOI: 10.3389/fenrg.2023.1125861.
   Web of Science ®Google Scholar
• I. Grcić and H. Pandžić, “Artificial Neural Network for High-Impedance-Fault Detection in DC Microgrids,” In 2023 IEEE PES Conference on Innovative Smart Grid Technologies-Middle East (ISGT Middle East), 2023. March. pp. 1–5. IEEE.
   Google Scholar
• K. Moloi and H. M. Langa, “High Impedance Fault Detection Scheme with the Penetration of Distributed Generation,” 2023 International Conference on Science, Engineering and Business for Sustainable Development Goals (SEB-SDG), IEEE, April, 2023, Vol. 1, pp. 1–6. DOI: 10.1109/SEB-SDG57117.2023.10124563.
   Google Scholar
• K. Yang, “Deep Learning for Power Flow Estimation and High Impedance Fault Detection,” Doctoral dissertation, University of Denver, 2023.
   Google Scholar
• Q. Meng, G. Zu, B. Li, W. Yao, L. Xu and J. Zhao, 2023. High impedance fault detection based on kurtosis and skewness coefficients. Available at SSRN 4353945
   Google Scholar
• G. Paramo, A. Bretas and S. Meyn, “High-Impedance Non-Linear Fault Detection via Eigenvalue Analysis with low PMU Sampling Rates,” 2023 IEEE Power & Energy Society Innovative Smart Grid Technologies Conference (ISGT), January, 2023. pp. 1–5. IEEE. DOI: 10.1109/ISGT51731.2023.10066424.
   Google Scholar
• T. Biswal, S. K. Parida and S. Mishra, “A DT-CWT and data mining based approach for high impedance fault diagnosis in micro-grid system,” Procedia Comp. Sci., vol. 217, pp. 1570–1578, 2023. DOI: 10.1016/j.procs.2022.12.357.
   Google Scholar
• E. Albanna, A. H. Al-Rifaie and A. A. Abdullah Al-Karakchi, “High impedance fault detection in low voltage overhead distribution based wavelet and harmonic indices,” Przeglad Elektrotechniczny, vol. 99, no. 7 2023.
   Web of Science ®Google Scholar
• M. N. Allawi, A. N. Hussain and M. K. Wali, “A new approach to detecting high impedance fault in power distribution feeder based on signal processing hybrid technique and ANNs,” Int. J. Intelligent Engng. Syst., vol. 16, no. 5, 2023.
   Google Scholar
• C. Şolea, D. Toader, M. Vinţan, M. Greconici, D. Vesa and I. Tatai, “MATLAB Library for Simulation of High Impedance Faults in Distribution Networks and Related Protective Relay Behaviour Analysis,” 2023 13th International Symposium on Advanced Topics in Electrical Engineering (ATEE), IEEE, 2023. pp. 1–4. DOI: 10.1109/ATEE58038.2023.10108111.
   Google Scholar
• S. Sarangi, B. K. Sahu and P. K. Rout, “High-impedance fault identification and location by using mode decomposition integrated adaptive multi-kernel extreme learning machine technique for distributed generator-based microgrid,” Electr. Eng., vol. 105, no. 1, pp. 383–406, 2023. DOI: 10.1007/s00202-022-01658-6.
   Web of Science ®Google Scholar
• A. K. Dubey, A. Kumar and J. P. Mishra, “Robust adaptive active islanding detection with $\alpha $-axis disturbance injection under high impedance fault, unbalanced loading & phase failure in grid tied PV system,” IEEE J. Emerg. Sel. Top. Ind. Electron, vol. 4, no. 4, pp. 1213–1223, 2023. DOI: 10.1109/JESTIE.2023.3281254.
   Google Scholar
• A. Mohammadi, M. Jannati and M. Shams, “Using deep transfer learning technique to protect electrical distribution systems against high-impedance faults,” IEEE Syst. J., vol. 17, no. 2, pp. 3160–3171, 2023. DOI: 10.1109/JSYST.2023.3234655.
   Web of Science ®Google Scholar
• Z. Moravej and M. Ghahremani, “Detection of high impedance faults in distribution networks using stationary wavelet transform,” Energy Engng Manage., vol. 11, no. 3, pp. 54–65, 2023.
   Google Scholar
• S. Kv, S. Gupta and M. M. O, “Detection of high impedance faults in power lines using empirical mode decomposition with intelligent classification techniques,” Computers Elect. Engng., vol. 109, pp. 108770, 2023. DOI: 10.1016/j.compeleceng.2023.108770.
   Web of Science ®Google Scholar
• S. A. Alaei and Y. Damchi, “A new method based on the discrete time energy separation algorithm for high and low impedance faults detection in distribution systems,” Electric Power Syst. Res., vol. 218, pp. 109200, 2023. DOI: 10.1016/j.epsr.2023.109200.
   Web of Science ®Google Scholar
• C. Ozansoy, D. Gomes and M. Faulkner, “Visibility of vegetation high-impedance fault low-frequency and high-frequency signatures,” IEEE Trans. Power Delivery, vol. 38, no. 3, pp. 2236–2239, 2023. DOI: 10.1109/TPWRD.2023.3265513.
   Web of Science ®Google Scholar
• A. K. Pandey, N. Kishor, S. R. Mohanty and P. Samuel, “A reliable fault detection algorithm for distribution network with DG resources,” Electric Power Syst. Res., vol. 223, pp. 109548, 2023. DOI: 10.1016/j.epsr.2023.109548.
   Web of Science ®Google Scholar
• H. Liang, H. Li and G. Wang, “A single-phase-to-ground fault detection method based on the ratio fluctuation coefficient of the zero-sequence current and voltage differential in a distribution network,” IEEE Access, vol. 11, pp. 7297–7308, 2023. DOI: 10.1109/ACCESS.2023.3238072.
   Web of Science ®Google Scholar
• P. Sinha, et al., “Identification of cross-country fault with high impedance syndrome in transmission line using tunable Q wavelet transform,” Mathematics, vol. 11, no. 3, pp. 586, 2023. DOI: 10.3390/math11030586.
   Web of Science ®Google Scholar
• B. Deshmukh, D. K. Lal and S. Biswal, “A reconstruction based adaptive fault detection scheme for distribution system containing AC microgrid,” Int. J. Elect. Power Energy Syst., vol. 147, pp. 108801, 2023. DOI: 10.1016/j.ijepes.2022.108801.
   Web of Science ®Google Scholar
• M. Hojabri, S. Nowak and A. Papaemmanouil, “ML-based intermittent fault detection, classification, and branch identification in a distribution network,” Energies, vol. 16, no. 16, pp. 6023, 2023. DOI: 10.3390/en16166023.
   Web of Science ®Google Scholar
• S. K. Pirmani and M. A. Mahmud, “Advances on fault detection techniques for resonant grounded power distribution networks in bushfire prone areas: identification of faulty feeders, faulty phases, faulty sections, and fault locations,” Electric Power Syst. Res., vol. 220, pp. 109265, 2023. DOI: 10.1016/j.epsr.2023.109265.
   Web of Science ®Google Scholar
• J. B. Thomas, S. G. Chaudhari, K. V. Shihabudheen and N. K. Verma, “CNN-based transformer model for fault detection in power system networks,” IEEE Trans. Instrum. Meas., vol. 72, pp. 1–10, 2023. DOI: 10.1109/TIM.2023.3238059.
   PubMedGoogle Scholar
• E. K. Bindumol, “High impedance fault detection and control methods in ac microgrids: a review,” IEEE 19th India council international conference (INDICON), Cochin, India, 2022, pp. 1–6.
   Google Scholar
• M. Sarwar, F. Mehmood, M. Abid, A. Q. Khan, S. T. Gul and A. S. Khan, “High impedance fault detection and isolation in power distribution networks using support vector machines,” J. King Saud Univ.-Engng. Sci., vol. 32, no. 8, pp. 524–535, 2020. DOI: 10.1016/j.jksues.2019.07.001.
   Google Scholar
• P. R. Varghese, M. S. P. Subathra, C. Mathew, S. T. George and N. J. Sairamya, 2022, “High impedance fault arc modeling—a review,” In International Conference on Intelligent Solutions for Smart Grids & Smart Cities. Singapore: Springer Nature Singapore, pp. 163–181
   Google Scholar
• S. Lavanya, S. Prabakaran and N. A. Kumar, “Literature review: high impedance fault in power system and detection techniques,” Math. Statistician Engng. Appl., vol. 71, no. 3, pp. 944–958, 2022.
   Google Scholar
• M. Biswal, C. D. Prasad, P. Ray and N. Kishor, “Modified Complete ensemble empirical mode decomposition based HIF detection approach for microgrid system,” Int. J. Elect. Power Energy Syst., vol. 141, pp. 108254, 2022. DOI: 10.1016/j.ijepes.2022.108254.
   Web of Science ®Google Scholar
• G. N. Lopes, T. S. Menezes, G. G. Santos, G. G. L. H. P. C. Trondoli and J. C. M. Vieira, “High impedance fault detection based on harmonic energy variation via S-transform,” Int. J. Elect. Power Energy Syst., vol. 136, pp. 107681, 2022. DOI: 10.1016/j.ijepes.2021.107681.
   Web of Science ®Google Scholar
• K. Rai, F. Hojatpanah, F. B. Ajaei, J. M. Guerrero and K. Grolinger, “Deep learning for high-impedance fault detection and classification: transformer-CNN,” Neural Comput. Appl., vol. 34, no. 16, pp. 14067–14084, 2022. DOI: 10.1007/s00521-022-07219-z.
   Web of Science ®Google Scholar
• M. Afshar, M. Majidi, O. A. Gashteroodkhani and M. E. Amoli, “Analyzing performance of relays for high impedance fault (HIF) detection using hardware-in-the-loop (HIL) platform,” Electric Power Syst. Res., vol. 209, pp. 108027, 2022. DOI: 10.1016/j.epsr.2022.108027.
   Web of Science ®Google Scholar
• K. Yu, et al., “A novel method of high impedance fault detection and fault resistance calculation based on damping rate double-ended measurement for distribution network,” Int. J. Elect. Power Energy Syst., vol. 136, pp. 107686, 2022. DOI: 10.1016/j.ijepes.2021.107686.
   Web of Science ®Google Scholar
• Y. Liu, Y. Zhao, L. Wang, C. Fang, B. Xie and L. Cui, “High-impedance fault detection method based on feature extraction and synchronous data divergence discrimination in distribution networks,” J. Modern Power Syst. Clean Energy, vol. 11, no. 4, pp. 1235–1246, 2023. DOI: 10.35833/MPCE.2021.000411.
   Web of Science ®Google Scholar
• A. Mohammadi, M. Jannati and M. Shams, “A protection scheme based on conditional generative adversarial network and convolutional classifier for high impedance fault detection in distribution networks,” Electric Power Syst. Res., vol. 212, pp. 108633, 2022. DOI: 10.1016/j.epsr.2022.108633.
   Web of Science ®Google Scholar
• S. Silva, P. Costa, M. Gouvea, A. Lacerda, F. Alves and D. Leite, “High impedance fault detection in power distribution systems using wavelet transform and evolving neural network,” Electric Power Syst. Res., vol. 154, pp. 474–483, 2018. DOI: 10.1016/j.epsr.2017.08.039.
   Web of Science ®Google Scholar
• A. Wontroba, et al., “High-impedance fault detection on downed conductor in overhead distribution networks,” Electric Power Syst. Res., vol. 211, pp. 108216, 2022. DOI: 10.1016/j.epsr.2022.108216.
   Web of Science ®Google Scholar
• K. Moloi and I. Davidson, “High impedance fault detection protection scheme for power distribution systems,” Mathematics, vol. 10, no. 22, pp. 4298, 2022. DOI: 10.3390/math10224298.
   Web of Science ®Google Scholar
• M. Afshar, M. Majidi, O. A. Gashteroodkhani and M. E. Amoli, “High impedance fault detection in a practical platform using a real-time-digital simulator,” IEEE Texas Power and Energy Conference (TPEC), IEEE, 2022, pp. 1–6.
   Google Scholar
• L. Cui and Y. Liu, “High impedance fault detection method based on Data divergence in the distribution network,” IEEE Power & Energy Society General Meeting (PESGM), IEEE, 2022, pp. 1–6.
   Google Scholar
• S. Khond, V. Kale and M. S. Ballal, “A combined Data Mining and Machine Learning approach for High Impedance Fault Detection in Microgrids,” IEEE International Conference on Power Electronics, Smart Grid, and Renewable Energy (PESGRE), IEEE, 2022, pp. 1–7.
   Google Scholar
• X. Wang, J. Gao, X. Wei, L. Guo, G. Song and P. Wang, “Faulty feeder detection under high impedance faults for resonant grounding distribution systems,” IEEE Trans. Smart Grid, vol. 14, no. 3, pp. 1880–1895, 2023. DOI: 10.1109/TSG.2022.3216731.
   Web of Science ®Google Scholar
• A. Ahmadi, E. Aghajari and M. Zangeneh, “High-impedance fault detection in power distribution grid systems based on support vector machine approach,” Electr. Eng., vol. 104, no. 5, pp. 3659–3672, 2022. DOI: 10.1007/s00202-022-01544-1.
   Web of Science ®Google Scholar
• B. N. Sahoo and S. Kar, “High impedance fault detection in microgrid using sum of difference method,” 2022 IEEE students conference on engineering and systems (SCES), IEEE, 2022, pp. 01–04. DOI: 10.1109/SCES55490.2022.9887665.
   Google Scholar
• M. Bhatnagar, A. Yadav and A. Swetapadma, “A resilient protection scheme for common shunt fault and high impedance fault in distribution lines using wavelet transform,” IEEE Syst. J., vol. 16, no. 4, pp. 5281–5292, 2022. DOI: 10.1109/JSYST.2022.3172982.
   Web of Science ®Google Scholar
• K. S. V. Swarna, A. Vinayagam, M. B. J. Ananth, P. V. Kumar, V. Veerasamy and P. Radhakrishnan, “A KNN based random subspace ensemble classifier for detection and discrimination of high impedance fault in PV integrated power network,” Measurement, vol. 187, pp. 110333, 2022. DOI: 10.1016/j.measurement.2021.110333.
   Web of Science ®Google Scholar
• K. Moloi and I. Davidson, 2022. “High impedance fault detection protection scheme for power systems distribution networks,” Available at SSRN 4220973
   Google Scholar
• X. Wang, et al., “Faulty feeder detection based on the integrated inner product under high impedance fault for small resistance to ground systems,” Int. J. Elect. Power Energy Syst., vol. 140, pp. 108078, 2022. DOI: 10.1016/j.ijepes.2022.108078.
   Web of Science ®Google Scholar
• D. Feng, S. Hongfei, Z. Xiangjun, X. Fan, Z. Hang and Z. Yihan, “High impedance fault detection method based on sparsity of traveling wave full waveform energy distribution,” 2022 China International Conference on Electricity Distribution (CICED), IEEE, 2022, pp. 1566–1570. DOI: 10.1109/CICED56215.2022.9929011.
   Google Scholar
• A. Chandra, G. K. Singh and V. Pant, “High impedance fault detection of looped microgrid based on estimated differential energy using EMD-TKEO,” 2022 2nd Odisha International Conference on Electrical Power Engineering, Communication and Computing Technology (ODICON), IEEE, November, 2022, pp. 1–6. DOI: 10.1109/ODICON54453.2022.10010333.
   Google Scholar
• Z. Y. Guo, M. F. Guo and J. H. Gao, “High impedance fault semi-supervised detection of distribution networks based on tri-training and support vector machine,” 2022 IEEE 3rd China International Youth Conference on Electrical Engineering (CIYCEE), November, 2022, IEEE, pp. 1–6. DOI: 10.1109/CIYCEE55749.2022.9958950.
   Google Scholar
• O. A. Gashteroodkhani, M. Majidi and M. Etezadi-Amoli, “Fire hazard mitigation in distribution systems through high impedance fault detection,” Electric Power Syst. Res., vol. 192, pp. 106928, 2021. DOI: 10.1016/j.epsr.2020.106928.
   Web of Science ®Google Scholar
• T. Biswal and S. K. Parida, “Residual energy based high impedance fault detection and classification in microgrid system using variational mode decomposition and K-nearest neighbor classifier,” 2022 IEEE IAS Global Conference on Emerging Technologies (GlobConET), May, IEEE, 2022, pp. 649–654. DOI: 10.1109/GlobConET53749.2022.9872486.
   Google Scholar
• M. Karimi and N. Ghaffarzadeh, “High impedance fault detection based on current harmonic analysis using Chirp Z transform,” Energy Syst., vol. 13, no. 3, pp. 813–833, 2022. DOI: 10.1007/s12667-021-00431-1.
   Google Scholar
• M. Biswal, M. Mishra, V. K. Sood, R. C. Bansal and A. Y. Abdelaziz, “Savitzky-Golay Filter integrated matrix pencil method to identify high impedance fault in a renewable penetrated distribution system,” Electric Power Syst. Res., vol. 210, pp. 108056, 2022. DOI: 10.1016/j.epsr.2022.108056.
   Web of Science ®Google Scholar
• J. G. S. Carvalho, A. R. Almeida, D. D. Ferreira, B. F. dos Santos, Jr, L. H. P. Vasconcelos and D. de Oliveira Sobreira, “High-impedance fault modeling and classification in power distribution networks,” Electric Power Syst. Res., vol. 204, pp. 107676, 2022. DOI: 10.1016/j.epsr.2021.107676.
   Web of Science ®Google Scholar
• V. Swarnkar, K. S. Diwan, M. Singh and S. Ralhan, “Machine learning based high impedance fault diagnosis in microgrid,” In 2022 Second International Conference on Advances in Electrical, Computing, Communication and Sustainable Technologies (ICAECT), IEEE, April, 2022, pp. 1–4. DOI: 10.1109/ICAECT54875.2022.9807880.
   Google Scholar
• P. I. Obi, E. A. Amako and C. S. Ezeonye, “High impedance fault arc analysis on 11 kV distribution networks,” Nig. J. Technol. Dev., vol. 19, no. 2, pp. 143–149, 2022. DOI: 10.4314/njtd.v19i2.6.
   Google Scholar
• J. Sun, X. Zhang, S. Wei, Q. Luo, Y. Hu and Q. Yang, “High-impedance fault location method of three-phase distribution lines based on electromagnetic time reversal,” Electric Power Syst. Res., vol. 212, pp. 108629, 2022. DOI: 10.1016/j.epsr.2022.108629.
   Web of Science ®Google Scholar
• C. D. Prasad, M. Biswal, M. Mishra, J. M. Guerrero and O. P. Malik, “Optimal threshold-based high impedance arc fault detection approach for renewable penetrated distribution system,” IEEE Syst. J., vol. 17, no. 2, pp. 2971–2981, 2023. DOI: 10.1109/JSYST.2022.3202809.
   Web of Science ®Google Scholar
• S. Lavanya, S. Prabakaran and N. A. Kumar, “Behavioral dynamics of high impedance fault under different line parameters,” Energy, vol. 9, pp. 12, 2022.
   Google Scholar
• H. Ding, Q. Huai, J. Wang, S. Zhu, Y. Li and Z. Hu, “A novel high-impedance fault recognition method for multi-terminal HVDC system,” 2022 IEEE Global Conference on Computing, Power and Communication Technologies (GlobConPT), IEEE, September, 2022, pp. 1–6. DOI: 10.1109/GlobConPT57482.2022.9938185.
   Google Scholar
• R. J. Sumaya, H. Mo, D. Dong and H. Pota, “High Impedance Fault Characterization on Single-Wire Earth Return Systems using Powerline Communication,” 2022 IEEE PES 14th Asia-Pacific Power and Energy Engineering Conference (APPEEC), IEEE, November, 2022, pp. 1–6. DOI: 10.1109/APPEEC53445.2022.10072268.
   Google Scholar
• S. Das, W. B. Agarpara and P. B. Deb, 2022. Analysis of High Impedance Fault in IEEE 9 Bus System by Signal Processing Tools Using MATLAB/Simulink Model (No. 7551). EasyChair.
   Google Scholar
• A. Soheili and J. Sadeh, “Evidential reasoning based approach to high impedance fault detection in power distribution systems,” IET Gen. Transmission Distrib., vol. 11, no. 5, pp. 1325–1336, 2017. DOI: 10.1049/iet-gtd.2016.1657.
   Web of Science ®Google Scholar
• Y.-S. Ko, “A self-isolation method for the HIF zone under the network-based distribution system,” IEEE Trans. Power Deliv., vol. 24, no. 2, pp. 884–891, 2009.
   Web of Science ®Google Scholar
• K. Sekar and N. K. Mohanty, “A fuzzy rule base approach for High Impedance Fault detection in distribution system using Morphology Gradient filter,” “n,” J. King Saud Univ.-Engng. Sci., vol. 32, no. 3, pp. 177–185, 2020. DOI: 10.1016/j.jksues.2018.12.001.
   Google Scholar
• T. M. Lai, L. A. Snider, E. Lo, C. H. Cheung and K. W. Chan, “High impedance faults detection using artificial neural network,” pp, pp. 821–826, 2003.
   Google Scholar
• J. J. G. Ledesma, K. B. do Nascimento, L. R. de Araujo and D. R. R. Penido, “A two-level ANN-based method using synchronized measurements to locate high-impedance fault in distribution systems,” Electric Power Syst. Res., vol. 188, pp. 106576, 2020. DOI: 10.1016/j.epsr.2020.106576.
   Web of Science ®Google Scholar
• M. S. R. Fernando, Spatio-Temporal Neural Networks in High-Impedance Fault Detection. Texas: Texas A&M University, 1994,
   Google Scholar
• T. Hubana, M. Saric and S. Avdaković, “Approach for identification and classification of HIFs in medium voltage distribution networks,” IET Generation, Trans. Distrib., vol. 12, no. 5, pp. 1145–1152, 2018. DOI: 10.1049/iet-gtd.2017.0883.
   Web of Science ®Google Scholar
• S. R. Samantaray, B. K. Panigrahi and P. K. Dash, “High impedance fault detection in power distribution networks using time–frequency transform and probabilistic neural network,” IET Gener. Transm. Distrib., vol. 2, no. 2, pp. 261–270, 2008. DOI: 10.1049/iet-gtd:20070319.
   Web of Science ®Google Scholar
• K. Rai, F. Hojatpanah, F. B. Ajaei and K. Grolinger, “Deep learning for high-impedance fault detection: convolutional autoencoders,” Energies, vol. 14, no. 12, pp. 3623, 2021. DOI: 10.3390/en14123623.
   Web of Science ®Google Scholar
• T. Sirojan, S. Lu, B. T. Phung, D. Zhang and E. Ambikairajah, “Sustainable deep learning at grid edge for real-time high impedance fault detection,” IEEE Trans. Sustain. Comput., vol. 7, no. 2, pp. 346–357, 2022. DOI: 10.1109/TSUSC.2018.2879960.
   Google Scholar
• A. A. Sheikh, S. A. Wakode, R. R. Deshmukh and M. S. Ballal, “Detection of High Impedance Fault in DC Microgrid,” 2020 IEEE International Conference on Power Electronics, Drives and Energy Systems (PEDES), IEEE, December, 2020, pp. 1–4. DOI: 10.1109/PEDES49360.2020.9379409.
   Google Scholar
• V. Torres, S. Maximov, H. F. Ruiz and J. L. Guardado, “Distributed parameters model for high-impedance fault detection and localization in transmission lines,” Electric Power Components Syst., vol. 41, no. 14, pp. 1311–1333, 2013. DOI: 10.1080/15325008.2013.823256.
   Web of Science ®Google Scholar
• C. Ozansoy, “Performance analysis of skewness methods for asymmetry detection in high impedance faults,” IEEE Trans. Power Syst., vol. 35, no. 6, pp. 4952–4955, 2020. DOI: 10.1109/TPWRS.2020.3018634.
   Web of Science ®Google Scholar
• F. P. Souza, L. F. Q. Silveira, F. B. Costa and M. M. Leal, “High-impedance fault identification using cyclostationary characteristic analysis,” Electric Power Syst. Res., vol. 195, pp. 107150, 2021. DOI: 10.1016/j.epsr.2021.107150.
   Web of Science ®Google Scholar
• S. R. Nam, J. K. Park, Y. C. Kang and T. H. Kim, “A modeling method of a high impedance fault in a distribution system using two series time-varying resistances in EMTP,” Power Engineering Society Summer Meeting. Conference Proceedings, Columbus, Ohio USA: IEEE, 2001, vol. 2, pp. 1175–1180.
   Google Scholar
• R. Ferraz, et al., “High impedance fault detection in distribution systems: adaptive approach considering noising environment,” 23rd International Conference & Exhibition on Electricity Distribution, 15–18 June, 2015, pp. 15–18.
   Google Scholar
• K. Moloi, J. A. Jordaan and Y. Hamam, “A hybrid method for high impedance fault classification and detection,” Southern African Universities Power Engineering Conference/Robotics and Mechatronics/Pattern Recognition Association of South Africa (SAUPEC/RobMech/PRASA), IEEE: Bloemfontein, South Africa, 2019, pp. 548–552.
   Google Scholar
• G. N. Lopes, V. A. Lacerda, J. C. M. Vieira and D. V. Coury, “Analysis of signal processing techniques for high impedance fault detection in distribution systems,” IEEE Trans. Power Delivery, vol. 36n, no. 6, pp. 3438–3447, 2021. DOI: 10.1109/TPWRD.2020.3042734.
   Web of Science ®Google Scholar
• A. Nakho, K. Moloi and Y. Hamam, “High impedance fault detection based on HS-transform and decision tree techniques,” 2021 Southern African Universities Power Engineering Conference/Robotics and Mechatronics/Pattern Recognition Association of South Africa (SAUPEC/RobMech/PRASA), IEEE, January, 2021, pp. 1–5. DOI: 10.1109/SAUPEC/RobMech/PRASA52254.2021.9377236.
   Google Scholar
• V. Gogula, B. Edward, K. Sathish Kumar, I. Jacob Raglend, K. Suvvala Jayaprakash and R. Sarjila, “High-Impedance Fault Localization Analysis Employing a Wavelet-Fuzzy Logic Approach,” In International Conference on Advances in Data-Driven Computing and Intelligent Systems, Singapore: Springer Nature Singapore, 2022, pp. 431–444.
   Google Scholar
• K. V. Shihabudheen, 2022. “Detection of high impedance fault using advanced ELM-based neuro-fuzzy inference system,” In Control and Measurement Applications for Smart Grid: Select Proceedings of SGESC 2021, Singapore: Springer Nature Singapore, pp. 397–408.
   Google Scholar
• M. Bhatnagar, A. Yadav and A. Swetapadma, “Fuzzy based relaying scheme for high impedance faults in DG integrated distribution system,” Electric Power Syst. Res., vol. 202, pp. 107602, 2022. DOI: 10.1016/j.epsr.2021.107602.
   Web of Science ®Google Scholar
• S. Wang and P. Dehghanian, “On the use of artificial intelligence for high impedance fault detection and electrical safety,” IEEE Trans. Ind. Applicat, vol. 56, no. 6, pp. 7208–7216, 2020. DOI: 10.1109/TIA.2020.3017698.
   Web of Science ®Google Scholar
• A. Kumar and V. Mehar, “Intelligent high impedance fault detection technique in power distribution network,” Research Journal of Engineering Technology and Medical Sciences (ISSN: 2582-6212), vol. 3, no. 04, 2020.
   Google Scholar
• Z. Cui, L. Du, P. Wang, X. Cai and W. Zhang, “Malicious code detection based on CNNs and multi-objective algorithm,” J. Parallel Distributed Computing, vol. 129, pp. 50–58, 2019. DOI: 10.1016/j.jpdc.2019.03.010.
   Web of Science ®Google Scholar
• S. Lavanya, S. Prabakaran and N. A. Kumar, “A deep learning technique for detecting high impedance faults in medium voltage distribution networks,” Eng. Technol. Appl. Sci. Res, vol. 12, no. 6, pp. 9477–9482, 2022. DOI: 10.48084/etasr.5288.
   Web of Science ®Google Scholar
• M. M. Eissa, M. H. Awadalla and A. M. Sharaf, 2021, “A new high impedance fault detection technique using deep learning neural network,” In Artificial Intelligence Applications in Electrical Transmission and Distribution Systems Protection, Boca Raton: CRC Press, pp. 179–195.
   Google Scholar
• X. Yibin, Q. Li and D. T. W. Chan, “DSP implementation of a wavelet analysis filter bank for high impedance fault detection,” International Conference on Energy Management and Power Delivery, Vol. 2, Paris, France: IEEE, 1998, pp. 417–421.
   Google Scholar
• Y. Abdullah, et al., “Hurst-exponent-based detection of high-impedance DC Arc events for 48-V systems in vehicles,” IEEE Trans. Power Electron, vol. 36n, no. 4, pp. 3803–3813, 2021. DOI: 10.1109/TPEL.2020.3020587.
   Web of Science ®Google Scholar
• J. Xi, X. Pei, W. Song, B. Xiang, Z. Liu and X. Zeng, “Experimental tests of DC SFCL under low impedance and high impedance fault conditions,” IEEE Trans. Appl. Supercond., vol. 31, no. 5, pp. 1–5, 2021. DOI: 10.1109/TASC.2021.3065886.
   Web of Science ®Google Scholar
• Q. Cui and Y. Weng, “Enhance high impedance fault detection and location accuracy via $\mu $-PMUs,” IEEE Trans. Smart Grid, vol. 11, no. 1, pp. 797–809, 2020. DOI: 10.1109/TSG.2019.2926668.
   Web of Science ®Google Scholar
• N. Bayati, et al., “Locating high-impedance faults in DC microgrid clusters using support vector machines,” Appl. Energy, vol. 308, pp. 118338, 2022. DOI: 10.1016/j.apenergy.2021.118338.
   Web of Science ®Google Scholar
• H. Wu, “Study of High Impedance Fault Characteristics and Detection Methods,” Doctoral dissertation. UNSW Sydney, 2015.
   Google Scholar
• A. P. Leão, J. P. A. Vieira, W. R. Heringer, A. L. Sousa, R. B. Gadelha and M. C. Santos, “Experimental investigation of high impedance faults in MV overhead distribution networks due to mango tree branches,” Simpósio Brasileiro de Sistemas Elétricos-SBSE, vol. 2, no. 1, 2022.
   Google Scholar
• E. D. Kilian, et al., “A Novel Method to Detect High Impedance Faults Using Time and Frequency Domains Characteristics,” In 2022 IEEE PES Generation, Transmission and Distribution Conference and Exposition–Latin America (IEEE PES GTD Latin America), IEEE, 2022, pp. 1–6.
   Google Scholar
• S. Silva, P. Costa, M. Santana and D. Leite, “Evolving neuro-fuzzy network for real-time high impedance fault detection and classification,” Neural Comput Appl., vol. 32, no. 12, pp. 7597–7610, 2020. DOI: 10.1007/s00521-018-3789-2.
   Web of Science ®Google Scholar
• N. Q. E. Mahathir and M. A. M. Ariff, “High impedance fault detection algorithm using frequency-based principal component analysis,” Evolution Elect. Electron. Engng., vol. 2, no. 2, pp. 540–546, 2021.
   Google Scholar
• S. Koley, S. Chattopadhyay, S. A. Hamim and S. Debnath, “High Impedance Single Line to Ground Fault Detection and Wavelet-alienation Based Faulty Phase Identification,” 2022 IEEE 6th International Conference on Condition Assessment Techniques in Electrical Systems (CATCON), IEEE, December, 2022. pp. 182–186. DOI: 10.1109/CATCON56237.2022.10077667.
   Google Scholar
• L. Jing, T. Zhao, L. Xia and J. Zhou, “An improved high-resistance fault detection method in DC microgrid based on orthogonal wavelet decomposition,” Appl. Sci., vol. 13, no. 1, pp. 393, 2022. DOI: 10.3390/app13010393.
   Google Scholar
• N. Vineeth and P. Sreejaya, 2020. “High impedance fault detection in low voltage distribution systems using wavelet and harmonic fault indices,” In 2020 IEEE International Conference on Power Electronics, Smart Grid and Renewable Energy (PESGRE2020), IEEE, pp. 1–6.
   Google Scholar
• Á. L. de Sousa, et al., “Harmonic analysis of high-impedance fault experimental current waveforms using fast Fourier transform,” Simpósio Brasileiro de Sistemas Elétricos-SBSE, vol. 2, no. 1, 2022.
   Google Scholar
• É. M. Lima, R. de Almeida Coelho, N. S. D. Brito and B. A. de Souza, “High impedance fault detection method for distribution networks under non-linear conditions,” Int. J. Elect. Power Energy Syst., vol. 131, pp. 107041, 2021. DOI: 10.1016/j.ijepes.2021.107041.
   Web of Science ®Google Scholar
• Y. Zhang, X. Wang, Y. Luo, Y. Xu, J. He and G. Wu, “A CNN based transfer learning method for high impedance fault detection,” 2020 IEEE Power & Energy Society General Meeting (PESGM), IEEE, August, 2020, pp. 1–5. DOI: 10.1109/PESGM41954.2020.9281671.
   Google Scholar
• T. R. Althi, E. Koley and S. Ghosh, “An optimally tuned rotation forest-based local protection scheme for detecting high-impedance faults in six-phase transmission line during nonlinear loading,” Iran J. Sci. Technol. Trans. Electr. Eng., vol. 46, no. 4, pp. 1129–1147, 2022. DOI: 10.1007/s40998-022-00515-3.
   Web of Science ®Google Scholar
• S. Vlahinić, D. Franković, B. Juriša and Z. Zbunjak, “Back up protection scheme for high impedance faults detection in transmission systems based on synchrophasor measurements,” IEEE Trans. Smart Grid, vol. 12, no. 2, pp. 1736–1746, 2021. DOI: 10.1109/TSG.2020.3031628.
   Web of Science ®Google Scholar
• B. Taheri and S. A. Hosseini, “Detection of high impedance fault in DC microgrid using impedance prediction technique,” 2020 15th International Conference on Protection and Automation of Power Systems (IPAPS), December, 2020, pp. 68–73. IEEE. DOI: 10.1109/IPAPS52181.2020.9375543.
   Google Scholar
• D. K. Dash, T. Biswal and S. C. Swain, “Optimum Relaying Scheme of High Impedance Fault Detection in Micro-Grid,” 2020 National Conference on Emerging Trends on Sustainable Technology and Engineering Applications (NCETSTEA), IEEE, February, 2020, pp. 1–6. DOI: 10.1109/NCETSTEA48365.2020.9119919.
   Google Scholar
• B. Wang and X. Cui, “Nonlinear modeling analysis and arc high-impedance faults detection in active distribution networks with neutral grounding via Petersen coil,” IEEE Trans. Smart Grid, vol. 13, no. 3, pp. 1888–1898, 2022. DOI: 10.1109/TSG.2022.3147044.
   Web of Science ®Google Scholar
• J. Zhu, T. Haiguo, H. Leng, J. Sun and C. Huang, “High impedance grounding fault detection in resonance grounding system based on nonlinear distortion of zero-sequence current,” 2020 5th International Conference on Smart Grid and Electrical Automation (ICSGEA), IEEE, June, 2020, pp. 74–78. DOI: 10.1109/ICSGEA51094.2020.00024.
   Google Scholar
• M. Wei, H. Zhang, F. Shi, W. Chen and V. Terzija, “Nonlinearity characteristic of high impedance fault at resonant distribution networks: theoretical basis to identify the faulty feeder,” IEEE Trans. Power Delivery, vol. 37, no. 2, pp. 923–936, 2022. DOI: 10.1109/TPWRD.2021.3074368.
   Web of Science ®Google Scholar
• J. C. Gu, Z. J. Huang, J. M. Wang, L. C. Hsu and M. T. Yang, “High impedance fault detection in overhead distribution feeders using a DSP-based feeder terminal unit,” IEEE Trans. Ind. Appl., vol. 57, no. 1, pp. 179–186, 2021. DOI: 10.1109/TIA.2020.3029760.
   Web of Science ®Google Scholar
• G. N. Lopes, L. H. Trondoli and J. C. Vieira, “Configuration and analysis of a high impedance fault simulation model,” EasyChair, vol. p.9 2022.
   Google Scholar
• L. H. P. C. Trondoli, G. N. Lopes and J. C. M. Vieira, “Configurable stochastic model for high impedance faults simulations in electrical distribution systems,” Electric Power Syst. Res., vol. 205, pp. 107686, 2022. DOI: 10.1016/j.epsr.2021.107686.
   Web of Science ®Google Scholar
• M. Wei, F. Shi, H. Zhang and W. Chen, “Wideband synchronous measurement-based detection and location of high impedance fault for resonant distribution systems with integration of DERs,” IEEE Trans. Smart Grid, vol. 14, no. 2, pp. 1117–1134, 2023. DOI: 10.1109/TSG.2022.3199781.
   Web of Science ®Google Scholar
• G. N. Lopes, T. S. Menezes and J. C. M. Vieira, “Evaluation of Metrics to Detect High Impedance Faults Using Real Current Signals,” 2022 20th International Conference on Harmonics & Quality of Power (ICHQP), IEEE, May, 2022, pp. 1–6. DOI: 10.1109/ICHQP53011.2022.9808554.
   Google Scholar
• X. Wang, X. Wei, J. Gao, G. Song, M. Kheshti and L. Guo, “High-impedance fault detection method based on stochastic resonance for a distribution network with strong background noise,” IEEE Trans. Power Delivery, vol. 37, no. 2, pp. 1004–1016, 2022. DOI: 10.1109/TPWRD.2021.3075472.
   Web of Science ®Google Scholar
• A. T. Langeroudi and M. M. Abdelaziz, “Preventative high impedance fault detection using distribution system state estimation,” Electric Power Syst. Res., vol. 186, pp. 106394, 2020. DOI: 10.1016/j.epsr.2020.106394.
   Web of Science ®Google Scholar
• G. Paramo and A. S. Bretas, “WAMS based eigenvalue space model for high impedance fault detection,” Appl. Sci., vol. 11, no. 24, pp. 12148, 2021. DOI: 10.3390/app112412148.
   Google Scholar
• J. Doria-García, C. Orozco-Henao, R. Leborgne, O. D. Montoya and W. Gil-González, “High impedance fault modeling and location for transmission line☆,” Electric Power Syst. Res., vol. 196, pp. 107202, 2021. DOI: 10.1016/j.epsr.2021.107202.
   Web of Science ®Google Scholar
• S. Nezamzadeh-Ejieh and I. Sadeghkhani, “High-impedance fault detection in distribution networks based on kullback-leibler divergence,” IET Generation Transmission Distribution, vol. 14, no. 1, pp. 1–9, 2020.
   Web of Science ®Google Scholar
• M. J. Ramos, M. Resener, A. S. Bretas, D. P. Bernardon and R. C. Leborgne, “Physics-based analytical model for high impedance fault location in distribution networks,” Electric Power Syst. Res., vol. 188, pp. 106577, 2020. DOI: 10.1016/j.epsr.2020.106577.
   Web of Science ®Google Scholar
• A. G. Rameshrao, E. Koley and S. Ghosh, “A LSTM-based approach for detection of high impedance faults in hybrid microgrid with immunity against weather intermittency and N-1 contingency,” Renewable Energy, vol. 198, pp. 75–90, 2022. DOI: 10.1016/j.renene.2022.08.028.
   Web of Science ®Google Scholar
• Y. M. Nsaif, M. S. Hossain Lipu, A. Hussain, A. Ayob, Y. Yusof and M. A. A. Zainuri, “A new voltage based fault detection technique for distribution network connected to photovoltaic sources using variational mode decomposition integrated ensemble bagged trees approach,” Energies, vol. 15, no. 20, pp. 7762, 2022. DOI: 10.3390/en15207762.
   Web of Science ®Google Scholar
• Y. M. Nsaif, M. S. Hossain Lipu, A. Hussain, A. Ayob, Y. Yusof and M. A. A. Zainuri, “A novel fault detection and classification strategy for photovoltaic distribution network using improved Hilbert–Huang transform and ensemble learning technique,” Sustainability, vol. 14, no. 18, pp. 11749, 2022. DOI: 10.3390/su141811749.
   Web of Science ®Google Scholar
• R. Bhandia, J. de Jesus Chavez, M. Cvetković and P. Palensky, “High impedance fault detection using advanced distortion detection technique,” IEEE Trans. Power Delivery, vol. 35, no. 6, pp. 1–1, 2020. DOI: 10.1109/TPWRD.2020.2973829.
   Web of Science ®Google Scholar
• D. P. S. Gomes and C. Ozansoy, “VeHIF: an accessible vegetation high-impedance fault data set format,” IEEE Trans. Power Delivery, vol. 37, no. 6, pp. 5473–5475, 2022. DOI: 10.1109/TPWRD.2022.3195002.
   Web of Science ®Google Scholar
• S. Khavari, R. Dashti, H. R. Shaker and A. Santos, “High impedance fault detection and location in combined overhead line and underground cable distribution networks equipped with data loggers,” Energies, vol. 13, no. 9, pp. 2331, 2020. DOI: 10.3390/en13092331.
   Web of Science ®Google Scholar
• D. Guillen, J. Olveres, V. Torres-García and B. Escalante-Ramírez, “Hermite transform based algorithm for detection and classification of high impedance faults,” IEEE Access, vol. 10, pp. 79962–79973, 2022. DOI: 10.1109/ACCESS.2022.3194525.
   Google Scholar
• Y. Zhang, X. Wang, J. He, Y. Xu, F. Zhang and Y. Luo, “A transfer learning-based high impedance fault detection method under a cloud-edge collaboration framework,” IEEE Access, vol. 8, pp. 165099–165110, 2020. DOI: 10.1109/ACCESS.2020.3022639.
   Google Scholar
• M. Faghihlou, B. Taheri and S. Salehimehr, “High impedance fault detection in dc microgrid using real and imaginary components of power,” 2020 28th Iranian Conference on Electrical Engineering (ICEE), IEEE, August, 2020, pp. 1–5. DOI: 10.1109/ICEE50131.2020.9260620.
   Google Scholar