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:: Volume 11, Issue 1 (4-2022) ::
ieijqp 2022, 11(1): 97-110 Back to browse issues page
A novel method to differentiate internal faults and inrush current in power transformers using adaptive sampling and Hilbert transform
Ali Akbar Nazari1 , Farzad Razavi * 1, Ahmad Fakharian1
1- Department of Electrical Engineering, Qazvin Branch, Islamic Azad University, Qazvin, Iran
Abstract:   (2728 Views)

One of the most important pieces of equipment in power systems is the power transformer. The main task of transformers is to change the voltage level in the system to deliver the generated energy to the final consumers. Power transformers are the main components of power systems because, without them, power transmission from the power plants to the consumers is not practically possible. Therefore, the importance of power transformers makes their protection a crucial issue. Differential relay is the relay most commonly used to protect power transformers throughout the world. Despite their many advantages, these types of relays may operate incorrectly during the magnetizing inrush current of the transformer and cause the healthy transformer to be separated from the power network. Thus, using some appropriate techniques to cope with this problem is necessary for power transformer protection. In a power network, the sampling rate can significantly impact the performance of the protection system. In this case, as the sampling rate increases, the computational complexity also rises. On the other hand, if the sampling rate decreases, it can reduce the accuracy of the protection system. Therefore, this paper presents a new method based on adaptive sampling and Hilbert transform to discriminate between inrush current and internal faults in a power transformer. The proposed method is also capable of detecting sympathetic inrush current. Besides, this method precisely detects various fault types and has an accurate performance when the current transformer is saturated, or the signal is noisy. The proposed method has been tested on a 230/63 kV transformer. The simulation results demonstrate that the proposed method has an appropriate performance during normal and sympathetic inrush currents. In addition, the proposed technique can distinguish between all fault types and inrush current in power transformers.
 

Keywords: Inrush current, Differential relay, Power system protection, Adaptive sampling
Full-Text [PDF 1057 kb]   (532 Downloads)    
Type of Study: Research |
Received: 2021/08/26 | Accepted: 2022/01/2 | Published: 2022/04/14
References
1. 521, A. R. "Technical reference manual of RET 521 ⁄ 2.3 (Transformer protection terminal). ABB relay catalogue-1MRK 504 016-UEN. .", ed.
2. Abniki, H., Monsef, H., Khajavi, P., & Dashti, H. (2010). A novel inductance-based technique for discrimination of internal faults from magnetizing inrush currents in power transformers. 2010 Modern Electric Power Systems,
3. Augustyniak, P. (2020). Adaptive sampling of the electrocardiogram based on generalized perceptual features. Sensors, 20(2), 373. [DOI:10.3390/s20020373]
4. Bainy, R. G., & Silva, K. M. (2020). Enhanced generalized alpha plane for numerical differential protection applications. IEEE Transactions on Power Delivery, 36(2), 587-597. [DOI:10.1109/TPWRD.2020.2985019]
5. Baoming, G., de Almeida, A. T., Qionglin, Z., & Xiangheng, W. (2005). An equivalent instantaneous inductance-based technique for discrimination between inrush current and internal faults in power transformers. IEEE Transactions on Power Delivery, 20(4), 2473-2482. [DOI:10.1109/TPWRD.2005.855443]
6. Barbosa, D., Netto, U. C., Coury, D. V., & Oleskovicz, M. (2011). Power transformer differential protection based on Clarke's transform and fuzzy systems. IEEE Transactions on Power Delivery, 26(2), 1212-1220. [DOI:10.1109/TPWRD.2010.2097281]
7. Behvandi, A., Seifossadat, S. G., & Saffarian, A. (2020). A new method for discrimination of internal fault from other transient states in power transformer using Clarke's transform and modified hyperbolic S-transform. Electric Power Systems Research, 178, 106023. [DOI:10.1016/j.epsr.2019.106023]
8. Bejmert, D., Rebizant, W., & Schiel, L. (2014). Transformer differential protection with fuzzy logic based inrush stabilization. International Journal of Electrical Power & Energy Systems, 63, 51-63. [DOI:10.1016/j.ijepes.2014.05.056]
9. Bi, D., Li, S., Wang, X., & Wang, W. (2008). A novel double-side average equivalent instantaneous inductance in nonsaturation zone based transformer protection. 2008 International Conference on Electrical Machines and Systems,
10. Dashti, H., Davarpanah, M., Sanaye-Pasand, M., & Lesani, H. (2016). Discriminating transformer large inrush currents from fault currents. International Journal of Electrical Power & Energy Systems, 75, 74-82. [DOI:10.1016/j.ijepes.2015.08.025]
11. Feldman, M. (2011). Hilbert transform in vibration analysis. Mechanical systems and signal processing, 25(3), 735-802. [DOI:10.1016/j.ymssp.2010.07.018]
12. Geethanjali, M., Slochanal, S. M. R., & Bhavani, R. (2008). PSO trained ANN-based differential protection scheme for power transformers. Neurocomputing, 71(4-6), 904-918. [DOI:10.1016/j.neucom.2007.02.014]
13. Gondane, P. R., Sheikh, R. M., Chawre, K. A., Wasnik, V. V., Badar, A., & Hasan, M. (2018). INRUSH CURRENT DETECTION USING WAVELET TRANSFORM AND ARTIFICIAL NEURAL NETWORK. 2018 Second International Conference on Computing Methodologies and Communication (ICCMC), [DOI:10.1109/ICCMC.2018.8487832]
14. Guzman, A., Zocholl, S., Benmouyal, G., & Altuve, H. J. (2002). A current-based solution for transformer differential protection. II. Relay description and evaluation. IEEE Transactions on Power Delivery, 17(4), 886-893. [DOI:10.1109/TPWRD.2002.803736]
15. Guzman, A., Zocholl, Z., Benmouyal, G., & Altuve, H. J. (2001). A current-based solution for transformer differential protection. I. Problem statement. IEEE Transactions on Power Delivery, 16(4), 485-491. [DOI:10.1109/61.956726]
16. Hahn, S. L. (1996). Hilbert transforms in signal processing. Artech House Signal Processing.
17. Hamida, S. B., Hmida, H., Borgi, A., & Rukoz, M. (2021). Adaptive sampling for active learning with genetic programming. Cognitive Systems Research, 65, 23-39. [DOI:10.1016/j.cogsys.2020.08.008]
18. Hong-ming, S., Tao, Z., Shao-feng, H., & Ou, L. (2014). Study on a Mal-opertaion case of differential protection due to the interaction between magnetizing inrush and sympathetic inrush. 2014 IEEE PES General Meeting| Conference & Exposition, [DOI:10.1109/PESGM.2014.6939046]
19. Horowitz, S. H., & Phadke, A. G. (2008). Power system relaying (Vol. 22). John Wiley & Sons. [DOI:10.1002/9780470758786]
20. Hosseini, S. A., Taheri, B., Abyaneh, H. A., & Razavi, F. (2021). Comprehensive power swing detection by current signal modeling and prediction using the GMDH method. Protection and Control of Modern Power Systems, 6(1), 1-11. [DOI:10.1186/s41601-021-00193-z]
21. Ibrahim, O. O., Zheng, T., & Zheng, X. (2018). Power transformer inrush current identification using relative wavelet energy. 2018 International Conference on Computer, Control, Electrical, and Electronics Engineering (ICCCEEE), [DOI:10.1109/ICCCEEE.2018.8515896]
22. Kagan, N., Ferrari, E., Matsuo, N., Duarte, S., Sanommiya, A., Cavaretti, J., Castellano, U., & Tenorio, A. (2000). Influence of rms variation measurement protocols on electrical system performance indices for voltage sags and swells. Ninth International Conference on Harmonics and Quality of Power. Proceedings (Cat. No. 00EX441), [DOI:10.1109/ICHQP.2000.896830]
23. Korpel, A. (1982). Gabor: frequency, time, and memory. Applied optics, 21(20), 3624-3632. [DOI:10.1364/AO.21.003624]
24. Medeiros, R., Costa, F., & Silva, K. (2015). Power transformer differential protection using the boundary discrete wavelet transform. IEEE Transactions on Power Delivery, 31(5), 2083-2095. [DOI:10.1109/TPWRD.2015.2513778]
25. P6, A. "Technical manual of P631, P632, P633, P634 (Transformer differential protection). AREVA relay catalogue-P63x/UK M/A54.," ed.
26. Pihler, J., Grcar, B., & Dolinar, D. (1997). Improved operation of power transformer protection using artificial neural network. IEEE Transactions on Power Delivery, 12(3), 1128-1136. [DOI:10.1109/61.636919]
27. Rad, I. S., Alinezhad, M., Naghibi, S. E., & Kamarposhti, M. A. (2011). Detection of internal fault in differential transformer protection based on fuzzy method. International Journal of Physical Sciences, 6(26), 6150-6158.
28. Rahmann, C., & Castillo, A. (2014). Fast frequency response capability of photovoltaic power plants: The necessity of new grid requirements and definitions. Energies, 7(10), 6306-6322. [DOI:10.3390/en7106306]
29. Roy, A., & Chakraborty, S. (2020). Support vector regression based metamodel by sequential adaptive sampling for reliability analysis of structures. Reliability Engineering & System Safety, 200, 106948. [DOI:10.1016/j.ress.2020.106948]
30. Sadeghi, M. H., Damchi, Y., & Shirani, H. (2018). Improvement of operation of power transformer protection system during sympathetic inrush current phenomena using fault current limiter. IET Generation, Transmission & Distribution, 12(22), 5968-5974. [DOI:10.1049/iet-gtd.2018.5697]
31. Sahebi, A., Samet, H., & Ghanbari, T. (2018). Identifying internal fault from magnetizing conditions in power transformer using the cascaded implementation of wavelet transform and empirical mode decomposition. International Transactions on Electrical Energy Systems, 28(2), e2485. [DOI:10.1002/etep.2485]
32. Salehimehr, S., Taheri, B., & Faghihlou, M. (2021). Detection of power swing and blocking the distance relay using the variance calculation of the current sampled data. Electrical Engineering, 1-15. [DOI:10.1007/s00202-021-01350-1]
33. Salehimehr, S., Taheri, B., Hosseini, S. A., Askarian Abyaneh, H., & Razavi, F. (2020). A new power swing detection method based on hilbert transform. International Journal of Industrial Electronics, Control and Optimization.
34. Shin, M.-C., Park, C.-W., & Kim, J.-H. (2003). Fuzzy logic-based relaying for large power transformer protection. IEEE Transactions on Power Delivery, 18(3), 718-724. [DOI:10.1109/TPWRD.2003.813598]
35. Sykes, J., & Morrison, I. (1972). A proposed method of harmonic restraint differential protecting of transformers by digital computer. IEEE Transactions on Power Apparatus and Systems(3), 1266-1272. [DOI:10.1109/TPAS.1972.293485]
36. Taheri, B., Faghihlou, M., Salehimehr, S., & Razavi, F. (2020). A fast Fourier transform-based method for power swing detection and distance relay malfunction prevention. Journal of Control, Automation and Electrical Systems, 31(6), 1458-1468. [DOI:10.1007/s40313-020-00638-0]
37. Taheri, B., Hosseini, S. A., Askarian-Abyaneh, H., & Razavi, F. (2020). A New Inrush Current Detection Method Based on Current Lissajous Figure. Journal of Intelligent Procedures in Electrical Technology (JIPET), 10(40), 43-56.
38. Taheri, B., Hosseini, S. A., Askarian‐Abyaneh, H., & Razavi, F. (2020). Power swing detection and blocking of the third zone of distance relays by the combined use of empirical‐mode decomposition and Hilbert transform. IET Generation, Transmission & Distribution, 14(6), 1062-1076. [DOI:10.1049/iet-gtd.2019.1167]
39. Taheri, B., Hosseini, S. A., & Salehimehr, S. An Energy Variation-Based Method for Discrimination Between the Internal Fault and Inrush Current in Power Transformers. 2020 14th International Conference on Protection and Automation of Power Systems (IPAPS),
40. Taheri, B., Hosseini, S. A., & Salehimehr, S. (2020). An Energy Variation-Based Method for Discrimination Between the Internal Fault and Inrush Current in Power Transformers. 2020 14th International Conference on Protection and Automation of Power Systems (IPAPS), [DOI:10.1109/IPAPS49326.2019.9069376]
41. Taheri, B., Hosseini, S. A., Salehimehr, S., & Razavi, F. A New Method for the End-To-End Testing of Differential Relays. 2020 14th International Conference on Protection and Automation of Power Systems (IPAPS),
42. Taheri, B., & Sedighizadeh, M. (2020). Detection of power swing and prevention of mal-operation of distance relay using compressed sensing theory. IET Generation, Transmission & Distribution, 14(23), 5558-5570. [DOI:10.1049/iet-gtd.2020.0540]
43. Taheri, B., & Sedighizadeh, M. (2021). A moving window average method for internal fault detection of power transformers. Cleaner Engineering and Technology, 100195. [DOI:10.1016/j.clet.2021.100195]
44. Tian, K., & Liu, P. (1998). Improved operation of differential protection of power transformers for internal faults based on negative sequence power. Proceedings of EMPD'98. 1998 International Conference on Energy Management and Power Delivery (Cat. No. 98EX137), [DOI:10.1109/EMPD.1998.702605]
45. Tripathy, M. (2010). Power transformer differential protection using neural network principal component analysis and radial basis function neural network. Simulation Modelling Practice and Theory, 18(5), 600-611. [DOI:10.1016/j.simpat.2010.01.003]
46. Wiszniewski, A., & Kasztenny, B. (1995). A multi-criteria differential transformer relay based on fuzzy logic. IEEE Transactions on Power Delivery, 10(4), 1786-1792. [DOI:10.1109/61.473379]
47. Zhalefar, F., & Sanaye-Pasand, M. (2010). A new fuzzy-logic-based extended blocking scheme for differential protection of power transformers. Electric Power Components and Systems, 38(6), 675-694. [DOI:10.1080/15325000903489678]
48. Ziegler, G. (2012). Numerical differential protection: principles and applications. John Wiley & Sons.


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Nazari A A, Razavi F, Fakharian A. A novel method to differentiate internal faults and inrush current in power transformers using adaptive sampling and Hilbert transform. ieijqp 2022; 11 (1) :97-110
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Volume 11, Issue 1 (4-2022) Back to browse issues page
نشریه علمی- پژوهشی کیفیت و بهره وری صنعت برق ایران Iranian Electric Industry Journal of Quality and Productivity
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