A Study for localization of fault in the electrical distribution systems
Main Article Content
Abstract
This article studies the location of faults in the electrical distribution system based on processing short-circuit signals. For this analysis, the simulation of cases using the CYME software is proposed, using the Wavelet transform to study the signal obtained and decomposed. The minimum spanning tree method is proposed so that fault location is optimal and reconnection time is minimal. This analysis considers the reclosers’ location in the distribution system that will serve as information repositories. In this investigation, a fault location algorithm was developed to analyse transient phenomena, achieving good precision in time frequency. Applying the proposed method, the signal is broken down into different levels, obtaining the necessary parameters to determine the distance of the fault.
Keywords
Fault detector, Short-circuit impedance, Wavelet transform, Fault location, Fault distance detector de fallas, impedancia de cortocircuito, transformada wavelet, localización de fallas, distancia de fallas
References
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[20] X. G. Magagula, Y. Hamam, J. A. Jordaan, and A. A. Yusuff, “A fault classification and localization method in a power distribution network,” 2017 IEEE AFRICON: Science, Technology and Innovation for Africa, AFRICON 2017, pp. 1337–1343, 11 2017. [Online]. Available: https://doi.org/10.1109/AFRCON.2017.8095676
[21] Z. Jianwen and D. Jiaxin, “Traveling wave fault location for lines combined with overhead-lines and cables based on empirical wavelet transform,” 2019 IEEE 2nd International Conference on Electronics and Communication Engineering, ICECE 2019, pp. 285–289, 12 2019. [Online]. Available: https://doi.org/10.1109/ICECE48499.2019.9058522
[22] Y. Jiang, “Data-driven probabilistic fault location of electric power distribution systems incorporating data uncertainties,” IEEE Transactions on Smart Grid, vol. 12, pp. 4522–4534, 9 2021. [Online]. Available: https://doi.org/10.1109/TSG.2021.3070550
[23] C. Zhang, G. Song, T.Wang, and L. Yang, “Singleended traveling wave fault location method in dc transmission line based on wave front information,” IEEE Transactions on Power Delivery, vol. 34, pp. 2028–2038, 10 2019. [Online]. Available: https://doi.org/10.1109/TPWRD.2019.2922654
[24] W. Pavón, E. Inga, and S. Simani, “Optimal routing an ungrounded electrical distribution system based on heuristic method with micro grids integration,” Sustainability, vol. 11, no. 6, 2019. [Online]. Available: https://doi.org/10.3390/su11061607
[25] M. A. Alotaibi and M. M. A. Salama, “An incentive-based multistage expansion planning model for smart distribution systems,” IEEE Transactions on Power Systems, vol. 33, no. 5, pp. 5469–5485, Sep. 2018. [Online]. Available: https://doi.org/10.1109/TPWRS.2018.2805322
[26] A. Valenzuela, E. Inga, and S. Simani, “Planning of a resilient underground distribution network using georeferenced data,” Energies, vol. 12, p. 644, 2 2019. [Online]. Available: https://doi.org/10.3390/EN12040644
[27] M. A. Syakur, B. K. Khotimah, E. M. S. Rochman, and B. D. Satoto, “Integration k-means clustering method and elbow method for identification of the best customer profile cluster,” IOP Conference Series: Materials Science and Engineering, vol. 336, p. 012017, apr 2018. [Online]. Available: https: //doi.org/10.1088/1757-899x/336/1/012017
[28] M. Mosbah, S. Arif, R. D. Mohammedi, and A. Hellal, “Optimum dynamic distribution network reconfiguration using minimum spanning tree algorithm,” in 2017 5th International Conference on Electrical Engineering – Boumerdes (ICEE-B), Oct 2017, pp. 1–6. [Online]. Available: https://doi.org/10.1109/ICEE-B.2017.8192170
[29] A. Guamán and A. Valenzuela, “Distribution network reconfiguration applied to multiple faulty branches based on spanning tree and genetic algorithms,” Energies, vol. 14, no. 20, 2021. [Online]. Available: https://doi.org/10.3390/en14206699
[30] G. Michau, N. Pustelnik, P. Borgnat, P. Abry, A. Nantes, A. Bhaskar, and E. Chung, “A primal-dual algorithm for link dependent origin destination matrix estimation,” IEEE Transactions on Signal and Information Processing over Networks, vol. 3, no. 1, pp. 104–113, March 2017. [Online]. Available: https://doi.org/10.1109/TSIPN.2016.2623094
[2] M. Gholami, A. Abbaspour, M. Moeini-Aghtaie, M. Fotuhi-Firuzabad, and M. Lehtonen, “Detecting the location of short-circuit faults in active distribution network using pmu-based state estimation,” IEEE Transactions on Smart Grid, vol. 11, pp. 1396–1406, 3 2020. [Online]. Available: https://doi.org/10.1109/TSG.2019.2937944
[3] S. Gururajapathy, H. Mokhlis, and H. Illias, “Fault location and detection techniques in power distribution systems with distributed generation: A review,” Renewable and Sustainable Energy Reviews, vol. 74, pp. 949–958, 2017. [Online]. Available: https://doi.org/10.1016/j.rser.2017.03.021
[4] S. H. Mortazavi, Z. Moravej, and S. M. Shahrtash, “A searching based method for locating high impedance arcing fault in distribution networks,” IEEE Transactions on Power Delivery, vol. 34, pp. 438–447, 4 2019. [Online]. Available: https://doi.org/10.1109/TPWRD.2018.2874879
[5] R. Dashti, M. Daisy, H. Mirshekali, H. R. Shaker, and M. Hosseini Aliabadi, “A survey of fault prediction and location methods in electrical energy distribution networks,” Measurement, vol. 184, p. 109947, 2021. [Online]. Available: https: //doi.org/10.1016/j.measurement.2021.109947
[6] M. Dashtdar, “Fault location in distribution network based on fault current analysis using artificial neural network,” International Journal of Electrical and Computer Sciences (IJECS), vol. 1, pp. 18–32, 10 2018. [Online]. Available: https://doi.org/10.33544/MJECE.V1I2.75
[7] J. Tavoosi, M. Shirkhani, A. Azizi, S. Ud Din, A. Mohammadzadeh, and S. Mobayen, “A hybrid approach for fault location in power distributed networks: Impedance-based and machine learning technique,” Electric Power Systems Research, vol. 210, p. 108073, 2022. [Online]. Available: https://doi.org/10.1016/j.epsr.2022.108073
[8] M. Azeroual, Y. Boujoudar, K. Bhagat, L. El Iysaouy, A. Aljarbouh, A. Knyazkov, M. Fayaz, M. S. Qureshi, F. Rabbi, and H. EL Markhi, “Fault location and detection techniques in power distribution systems with distributed generation: Kenitra city (morocco) as a case study,” Electric Power Systems Research, vol. 209, p. 108026, 2022. [Online]. Available: https://doi.org/10.1016/j.epsr.2022.108026
[9] Z. Jianwen, H. Hui, G. Yu, H. Yongping, G. Shuping, and L. Jianan, “Single-phase ground fault location method for distribution network based on traveling wave time-frequency characteristics,” Electric Power Systems Research, vol. 186, p. 106401, 2020. [Online]. Available: https://doi.org/10.1016/j.epsr.2020.106401
[10] J. Liang, T. Jing, H. Niu, and J. Wang, “Two-terminal fault location method of distribution network based on adaptive convolution neural network,” IEEE Access, vol. 8, pp. 54 035–54 043, 2020. [Online]. Available: https://doi.org/10.1109/ACCESS.2020.2980573
[11] P. Mrsic, v. Zeljkovic, D. Lekic, B. Erceg, P. Matic, S. Zubic, and P. Balcerek, “Minimization of power interruption time in mv distribution networks with fault locators based on optimal placement of fault passage indicators,” in 2018 International Symposium on Industrial Electronics (INDEL), Nov 2018, pp. 1–7. [Online]. Available: https://doi.org/10.1109/INDEL.2018.8637620
[12] X. Wang, H. Zhang, F. Shi, Q. Wu, V. Terzija, W. Xie, and C. Fang, “Location of single phase to ground faults in distribution networks based on synchronous transients energy analysis,” IEEE Transactions on Smart Grid, vol. 11, pp. 774–785, 1 2020. [Online]. Available: https://doi.org/10.1109/TSG.2019.2938667
[13] W. C. Santos, F. V. Lopes, N. S. Brito, and B. A. Souza, “High-impedance fault identification on distribution networks,” IEEE Transactions on Power Delivery, vol. 32, pp. 23–32, 2 2017. [Online]. Available: https://doi.org/10.1109/TPWRD.2016.2548942
[14] 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 Systems Research, vol. 154, pp. 474–483, 1 2018. [Online]. Available: https://doi.org/10.1016/J.EPSR.2017.08.039
[15] M. F. Guo, N. C. Yang, and L. X. You, “Wavelet-transform based early detection method for short-circuit faults in power distribution networks,” International Journal of Electrical Power & Energy Systems, vol. 99, pp. 706–721, 7 2018. [Online]. Available: https://doi.org/10.1016/J.IJEPES.2018.01.013
[16] F. M. Aboshady, D. W. Thomas, and M. Sumner, “A new single end wideband impedance based fault location scheme for distribution systems,” Electric Power Systems Research, vol. 173, pp. 263–270, 8 2019. [Online]. Available: https://doi.org/10.1016/J.EPSR.2019.04.034
[17] A. Silos-Sanchez, R. Villafafila-Robles, and P. Lloret-Gallego, “Novel fault location algorithm for meshed distribution networks with ders,” Electric Power Systems Research, vol. 181, p. 106182, 4 2020. [Online]. Available: https://doi.org/10.1016/J.EPSR.2019.106182
[18] S. Myint and W. Wichakool, “A traveling wavebased fault section and fault distance estimation algorithm for grounded distribution systems,” 2019 IEEE PES GTD Grand International Conference and Exposition Asia, GTD Asia 2019, pp. 472–477, 5 2019. [Online]. Available: https: //doi.org/10.1109/GTDASIA.2019.8715933
[19] P. Li, X. Liu, Z. Yuan, W. Chen, L. Yu, Q. Xu, and Y. Lin, “Precise fault location method of traveling wave in distribution grid based on multiple measuring point,” 2020 IEEE 4th Conference on Energy Internet and Energy System Integration: Connecting the Grids Towards a Low-Carbon High-Efficiency Energy System, EI2 2020, pp. 1867–1872, 10 2020. [Online]. Available: https://doi.org/10.1109/EI250167.2020.9346873
[20] X. G. Magagula, Y. Hamam, J. A. Jordaan, and A. A. Yusuff, “A fault classification and localization method in a power distribution network,” 2017 IEEE AFRICON: Science, Technology and Innovation for Africa, AFRICON 2017, pp. 1337–1343, 11 2017. [Online]. Available: https://doi.org/10.1109/AFRCON.2017.8095676
[21] Z. Jianwen and D. Jiaxin, “Traveling wave fault location for lines combined with overhead-lines and cables based on empirical wavelet transform,” 2019 IEEE 2nd International Conference on Electronics and Communication Engineering, ICECE 2019, pp. 285–289, 12 2019. [Online]. Available: https://doi.org/10.1109/ICECE48499.2019.9058522
[22] Y. Jiang, “Data-driven probabilistic fault location of electric power distribution systems incorporating data uncertainties,” IEEE Transactions on Smart Grid, vol. 12, pp. 4522–4534, 9 2021. [Online]. Available: https://doi.org/10.1109/TSG.2021.3070550
[23] C. Zhang, G. Song, T.Wang, and L. Yang, “Singleended traveling wave fault location method in dc transmission line based on wave front information,” IEEE Transactions on Power Delivery, vol. 34, pp. 2028–2038, 10 2019. [Online]. Available: https://doi.org/10.1109/TPWRD.2019.2922654
[24] W. Pavón, E. Inga, and S. Simani, “Optimal routing an ungrounded electrical distribution system based on heuristic method with micro grids integration,” Sustainability, vol. 11, no. 6, 2019. [Online]. Available: https://doi.org/10.3390/su11061607
[25] M. A. Alotaibi and M. M. A. Salama, “An incentive-based multistage expansion planning model for smart distribution systems,” IEEE Transactions on Power Systems, vol. 33, no. 5, pp. 5469–5485, Sep. 2018. [Online]. Available: https://doi.org/10.1109/TPWRS.2018.2805322
[26] A. Valenzuela, E. Inga, and S. Simani, “Planning of a resilient underground distribution network using georeferenced data,” Energies, vol. 12, p. 644, 2 2019. [Online]. Available: https://doi.org/10.3390/EN12040644
[27] M. A. Syakur, B. K. Khotimah, E. M. S. Rochman, and B. D. Satoto, “Integration k-means clustering method and elbow method for identification of the best customer profile cluster,” IOP Conference Series: Materials Science and Engineering, vol. 336, p. 012017, apr 2018. [Online]. Available: https: //doi.org/10.1088/1757-899x/336/1/012017
[28] M. Mosbah, S. Arif, R. D. Mohammedi, and A. Hellal, “Optimum dynamic distribution network reconfiguration using minimum spanning tree algorithm,” in 2017 5th International Conference on Electrical Engineering – Boumerdes (ICEE-B), Oct 2017, pp. 1–6. [Online]. Available: https://doi.org/10.1109/ICEE-B.2017.8192170
[29] A. Guamán and A. Valenzuela, “Distribution network reconfiguration applied to multiple faulty branches based on spanning tree and genetic algorithms,” Energies, vol. 14, no. 20, 2021. [Online]. Available: https://doi.org/10.3390/en14206699
[30] G. Michau, N. Pustelnik, P. Borgnat, P. Abry, A. Nantes, A. Bhaskar, and E. Chung, “A primal-dual algorithm for link dependent origin destination matrix estimation,” IEEE Transactions on Signal and Information Processing over Networks, vol. 3, no. 1, pp. 104–113, March 2017. [Online]. Available: https://doi.org/10.1109/TSIPN.2016.2623094
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Published
Nov 22, 2023
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Electrical Engineering
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