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:: Volume 10, Issue 4 (1-2022) ::
ieijqp 2022, 10(4): 1-13 Back to browse issues page
Detection of high impedance faults in distribution networks using Discrete Fourier Transform
Zahra Moravej * 1, Mehrdad Ghahremani1
1- Semnan University
Abstract:   (2401 Views)
This paper proposes a new method for extracting dynamic properties for high impedance fault (HIF) detection using discrete Fourier transform (DFT). Unlike conventional methods that use features extracted from data windows after fault to detect high impedance fault, in the proposed method, using the disturbance detection algorithm in the network, the normalized changes of the selected features are used to compare the data windows after the fault occurrence and before the fault occurrence. It also uses the post-disturbance data windows, develops a decision system based on the output of the support vector machines (SVM) classifier, and compares the amount of certainty of other network events with high impedance fault. The reliability and security of the proposed method have been improved. The proposed method is implemented on an IEEE 34 bus network in EMTP-RV software. The simulation results show 97.2% accuracy, 98.5% reliability, and 98.8% security..
Article number: 1
Keywords: High impedance fault, Discrete Fourier Transform, Fast Fourier Transform, Disturbance detection, distribution networks, Support Vector Machine.
Full-Text [PDF 2354 kb]   (627 Downloads)    
Type of Study: Research |
Received: 2020/12/8 | Accepted: 2021/10/2 | Published: 2021/12/2
References
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26. [1] Gadanayak, D. A. A Review on High-Impedance Ground Fault Detection Techniques in Distribution Networks. Green Technology for Smart City and Society, pp. 299-309.‌2021. [DOI:10.1007/978-981-15-8218-9_26]
27. [2] Tengdin, J., and Westfall, R., "High impedance fault detection technology", Report of PSRC Working Group D15, pp. 1-12, 1996.
28. [3] Benner, C.L., and Russell, B.D., "Practical high-impedance fault detection on distribution feeders", IEEE Trans. Ind. Appl, Vol. 33, No. 3, pp. 635-640, 1997. [DOI:10.1109/28.585852]
29. [4] Mamishev, A. V., Russell, B. D., and Benner, C. L. "Analysis of high impedance faults using fractal techniques", IEEE Trans. Power Syst, vol. 11, no. 1, pp. 435-440, 1996. [DOI:10.1109/59.486130]
30. [5] Ghaderi, A., Ginn III, H.L. and Mohammadpour, H.A., "High impedance fault detection: A review", Electr. Power Syst. Res., Vol. 143, pp. 376-388, 2017. [DOI:10.1016/j.epsr.2016.10.021]
31. [6] Sekar, K., and Mohanty, N.K., "A fuzzy rule base approach for High Impedance Fault detection in distribution system using Morphology Gradient filter", J. King Saud Univ. Eng. Sci, Vol. 32, No. 3, pp. 177-185, 2020. [DOI:10.1016/j.jksues.2018.12.001]
32. [7] Kavaskar. S., and Mohanty, N.K., "Detection of high impedance fault in distribution networks", Ain Shams Engineering Journal, vol. 10, no. 1, pp. 5-13, 2019. [DOI:10.1016/j.asej.2018.04.006]
33. [8] S. Silva, P. Costa, M. Sanatana and D. Leite, "Evolving neuro fuzzy network for real-time high impedance fault detection and classification," Neural Computing and Applications, vol. 32, no. 12, pp. 7597-7610, 2020. [DOI:10.1007/s00521-018-3789-2]
34. [9] Sekar, K., and Mohanty, N.K., "Data mining-based high impedance fault detection using mathematical morphology", Comput. Electr. Eng, Vol. 69, pp. 129-141, 2018. [DOI:10.1016/j.compeleceng.2018.05.010]
35. [10] Aziz, M.A., Hassan, M.M., and Zahab, E.A., "High-impedance faults analysis in distribution networks using an adaptive neuro fuzzy inference system", Electr. Power. Compon. Syst, Vol. 40, No. 11, pp. 1300-1318, 2012. [DOI:10.1080/15325008.2012.689418]
36. [11] Sahoo, S., and Baran, M.E., "A method to detect high impedance faults in distribution feeders", IEEE PES. Trans. Dis. Conf. Exposition, pp. 1-6, 2014. [DOI:10.1109/TDC.2014.6863531]
37. [12] Zhang, S., Xiao, X., and He, Z., "Detection of high‐impedance fault in distribution network based on time-frequency entropy of wavelet transform", IEEJ Trans. Electr. Electron. Eng, Vol. 15, No. 6, pp. 844-853, 2020. [DOI:10.1002/tee.23126]
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39. [14] Bhat, A. U. Q., Prakash, A., Tayal, V. K., and Choudekar, P., "High Impedance Fault Analysis of Distributed Power System Network Using Discrete Wavelet Transform", In Advances in Smart Communication and Imaging Systems,Springer, Singapore, pp.561-576, 2021. [DOI:10.1007/978-981-15-9938-5_53]
40. [15] Gadanayak, D.A., and Mallick, R.K., "Interharmonics based high impedance fault detection in distribution systems using maximum overlap wavelet packet transform and a modified empirical mode decomposition", Int. J. Electr. Power Energy Syst, Vol. 112, pp. 282-293, 2019. [DOI:10.1016/j.ijepes.2019.04.050]
41. [16] Silva, S., Costa, P., Gouvea, M., Lacerda, A., Alves, F., and Leite, D., "High impedance fault detection in power distribution systems using wavelet transform and evolving neural network", Electr. Power Syst, Vol. 154, pp. 474-483, 2018. [DOI:10.1016/j.epsr.2017.08.039]
42. [17] Moravej, Z., Mortazavi, S.H., and Shahrtash, S.M., "DT‐CWT based event feature extraction for high impedance faults detection in distribution system", Int Trans. Electr. Energ. Syst, Vol. 25, No. 12, pp. 3288-3303, 2015. [DOI:10.1002/etep.2035]
43. [18] Sarlak, M., and Shahrtash, S.M., "High impedance fault detection using combination of multi-layer perceptron neural networks based on multi-resolution morphological gradient features of current waveform", IET. Gener. Transm. Dis, Vol. 5, No. 5, pp. 588 - 595, 2011. [DOI:10.1049/iet-gtd.2010.0702]
44. [19] AsghariGovar. S., Pourghasem. P., and Seyedi. H., "High impedance fault protection scheme for smart grids based on WPT and ELM considering evolving and cross-country faults", Int. J. Electr. Power Energ Syst, vol. 107, pp. 412-421, 2019. [DOI:10.1016/j.ijepes.2018.12.019]
45. [20] Ghaderi, A., Mohammadpour, H.A., Ginn, H.L., and Shin, Y.J., "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]
46. [21] Mortazavi, S.H., Moravej, Z., and Shahrtash, S.M., "A hybrid method for arcing faults detection in large distribution networks", Int. J. Electr. Power Energ Syst, Vol. 94, pp. 141-150, 2018. [DOI:10.1016/j.ijepes.2017.06.036]
47. [22] Mohammadnian, Y., Amraee, T., and Soroudi, A., "Fault detection in distribution networks in presence of distributed generations using a data mining-driven wavelet transform", IET Smart Grid, Vol. 2, No. 2, pp. 163-171, 2019. [DOI:10.1049/iet-stg.2018.0158]
48. [23] Cui, Q., and Weng, Y., "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]
49. [24] Vapnik. V., and Chervonenkis. A., "The necessary and sufficient conditions for consistency in the empirical risk minimization method", Pattern Recogn Image Anal, vol. 1, no. 3, pp. 283 - 305, 1991.
50. [25] Distribution Test Feeders, IEEE PES Distribution System Analysis Subcommittee's, Distribution Test Feeder Working Group, August 2013.


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نشریه علمی- پژوهشی کیفیت و بهره وری صنعت برق ایران Iranian Electric Industry Journal of Quality and Productivity
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