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Non-communication protection scheme for power transmission system based on transient currents, HHT and SVM

Non-communication protection scheme for power transmission system based on transient currents, HHT and SVM

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How to improve the reliability has been a challenging task for transient protection, which has been affected seriously by the fault initial angle (FIA) and transient resistance (TR). Based on support vector machine (SVM), a novel smart transient protection method is presented in this study, which protects a bus and two transmission lines connected to the bus. The method is based on the measurements from the two close-in ends of the two lines. Hilbert–Huang transform is used to extracting instantaneous amplitude from the measured currents. The fault area is determined from the two instantaneous amplitude-integral (IA) of the transient fault currents, the difference of the two IAs, FIA, and the TR. SVM is utilised to determine the fault area. Two IAIs, difference of IAs, FIA and TR are treated as the input to SVMs. Faults with different FIA and TR are treated as a different class of fault, respectively. Correspondingly, a different criterion of discrimination is automatically employed by SVMs for a different fault class. The influence of FIA and TR is eliminated significantly, and the reliability of protection is enhanced substantially. The performance of the method is tested using ATP/EMTP with satisfactory results.

References

    1. 1)
      • 1. Bo, Z.Q., Weller, G., Dai, F.T., et al: ‘Transient based protection for transmission lines’, IEEE Power Syst. Tech., 1998, 2, pp. 10671071.
    2. 2)
      • 2. Bo, Z.Q.: ‘A new non-communication protection technique for transmission lines’, IEEE Trans. Power Deliv., 1998, 13, (3), pp. 10731078.
    3. 3)
      • 3. Bao-Hui, Z., Heng-Xu, H., Jian-Dong, D.: ‘Boundary protection – a new concept for extra high voltage transmission lines part II discriminative criterions and simulations’. IEEE/PES Transmission & Distribution Conference & Exposition: Asia and Pacific Dalian, China, 2005, pp. 15.
    4. 4)
      • 4. Zhang, N., Kezunovic, M.: ‘Transmission line boundary protection using wavelet transform and neural network’, IEEE Trans. Power Deliv., 2007, 22, (2), pp. 859869.
    5. 5)
      • 5. Duan, J., Jun, K., Wu, S.: ‘Boundary protection algorithm based on phase information of improved recursive wavelet transform for EHV transmission lines’. IEEE Power and Energy Engineering Conf., Asia-Pacific, Wuhan, China, 2009, pp. 14.
    6. 6)
      • 6. Wu, Q.H., Zhang, J.F., Zhang, D.J.: ‘Ultra-high-speed directional protection of transmission lines using mathematical morphology’, IEEE Trans. Power Deliv., 2003, 18, (4), pp. 11271133.
    7. 7)
      • 7. Dehghani, W.M., Khooban, M.H., Niknam, T.: ‘Fast fault detection and classification based on a combination of wavelet singular entropy theory and fuzzy logic in distribution lines in the presence of distributed generations’, Electr. Power Energy Syst., 2016, 78, pp. 455462.
    8. 8)
      • 8. Manori, A., Tripathy, M., Gupta, H.O.: ‘SVM based zonal setting of Mho relay for shunt compensated transmission line’, Electr. Power Energy Syst., 2016, 78, pp. 422428.
    9. 9)
      • 9. Fathabadi, H.: ‘Novel filter based ANN approach for short-circuit faults detection classification and location in power transmission lines’, Electr. Power Energy Syst., 2016, 74, pp. 374383.
    10. 10)
      • 10. Dubey, R., Samantaray, S.R., Panigrahi, B.K.: ‘An extreme learning machine based fast and accurate adaptive distance relaying scheme’, Electr. Power Energy Syst., 2015, 73, pp. 10021014.
    11. 11)
      • 11. Zhang, D.J., Wu, Q.H., Bo, Z.Q.: ‘Transient positional protection of transmission lines using complex wavelets analysis’, IEEE Trans. Power Deliv., 2003, 18, (3), pp. 705710.
    12. 12)
      • 12. Lin, X.N., Bo, Z.Q., Caunce, B.R.J., et al: ‘Boundary protection using complex wavelet transform’. Proc. 6th Int. Conf. Advances in Power System Control, Operation and Management, Hong Kong, China, November 2003, pp. 744749.
    13. 13)
      • 13. Hajjar, A.A.: ‘A high speed non communication protection scheme for power transmission lines based on wavelet transform’, Electr. Power Syst. Res., 2013, 96, pp. 194200.
    14. 14)
      • 14. Khodadadi, M., Shahrtash, S.M.: ‘A new noncommunication-based protection scheme for three-terminal transmission lines employing mathematical morphology-based filters’, IEEE Trans. Power Deliv., 2013, 28, (1), pp. 347356.
    15. 15)
      • 15. Duan, J.D., Zhang, B.H., Luo, S.B., et al: ‘Study of non-unit transient-based protection for EHV transmission lines using backward traveling-wave’. IEEE int. Conf. Power System Technology, 2006, pp. 17.
    16. 16)
      • 16. Mingchao, X., Yizhuang, H.: ‘Transient based protection using current transients’. IEEE Int. Conf. Power and Energy, Johor Baharu, Malaysia, December 2008, pp. 526530.
    17. 17)
      • 17. Guo, Z., Yao, J., Yang, S., et al: ‘A new method for non-unit protection of power transmission lines based on fault resistance and fault angle reduction’, Electr. Power Energy Syst., 2014, 55, pp. 760769.
    18. 18)
      • 18. Malathi, V., Marimuthu, N.S., Baskar, S.: ‘Intelligent approaches using support vector machine and extreme learning machine for transmission line protection’, Neurocomputing, 2010, 73, pp. 21602167.
    19. 19)
      • 19. Yusuff, A.A., Fei, C., Jimoh, A.A., et al: ‘Fault location in a series compensated transmission line based on wavelet packet decomposition and support vector regression’, Electr. Power Syst. Res., 2011, 81, pp. 12581265.
    20. 20)
      • 20. Ekici, S.: ‘Support vector machines for classification and locating faults on transmission lines’, Appl. Soft Comput., 2012, 12, pp. 16501658.
    21. 21)
      • 21. Jafarian, P., Sanaye-Pasand, M.: ‘High-frequency transients-based protection of multiterminal transmission lines using the SVM technique’, IEEE Trans. Power Deliv., 2013, 28, (1), pp. 188196.
    22. 22)
      • 22. Bernadić, A., Leonowicz, Z.: ‘Fault location in power networks with mixed feeders using the complex space-phasor and Hilbert-Huang transform’, Electr. Power Energy Syst., 2012, 42, pp. 208219.
    23. 23)
      • 23. Yalcin, T., Ozgonenel, O., Kurt, U.: ‘Feature vector extraction by using empirical mode decomposition for power quality disturbances’. 10th EEEIC Conf., Rome, May 2011, pp. 811.
    24. 24)
      • 24. Ozgonenel, O., Yalcin, T., Guney, I., et al: ‘A new classification for power quality events in distribution system’, Electr. Power Syst. Res., 2013, 95, (95), pp. 192199.
    25. 25)
      • 25. Yalcin, T., Ozgonenel, O., Kurt, U.: ‘Multi – class power quality disturbances classification by using ensemble empirical mode decomposition based SVM’. 7th Int. Conf. Electrical and Electronics Engineering, Turkey, December 2011, pp. 14.
    26. 26)
      • 26. Yang, Y., Yu, D., Cheng, J.: ‘A fault diagnosis approach for roller bearing based on IMF envelope spectrum and SVM’, Measurement, 2007, 40, pp. 943950.
    27. 27)
      • 27. Wang, Y.H., Yeh, C.H., Young, H.W.V., et al: ‘On the computational complexity of the empirical mode decomposition algorithm’, Physica A, Stat. Mech. Appl., 2014, 400, (15), pp. 159167.
    28. 28)
      • 28. Wu, Z., Huang, N.E.: ‘Ensemble empirical mode decomposition: a noise-assisted data analysis method’, Adv. Adapt. Data Anal., 2009, 1, pp. 141.
    29. 29)
      • 29. Yeh, J.R., Shieh, J.S., Huang, N.E.: ‘Complementary ensemble empirical mode decomposition: a novel noise enhanced data analysis method’, Adv. Adapt. Data Anal., 2010, 2, (2), pp. 135156.
    30. 30)
      • 30. Peng, Z.K., Tsea, P.W., Chu, F.L.: ‘A comparison study of improved Hilbert-Huang transform and wavelet transform: application to fault diagnosis for rolling bearing’, Mech. Syst. Signal Process., 2005, 19, pp. 974988.
    31. 31)
      • 31. Phdakle, A.G., Thorp, J.S.: ‘Computer relaying for power systems’ (John Wiley & Sons, Baldock, UK, 2009, 2nd edn.).
    32. 32)
      • 32. Fei, X., Xinzhou, D., Bin, W., et al: ‘Combined single-end fault location method of transmission line and its experiments’, Electr. Power Autom. Equip., 2014, 34, (4), pp. 3742.
    33. 33)
      • 33. Hua-Zhong, Z., Wei-Qing, W., Ling-Ling, Z., et al: ‘Ground distance relay based on fault resistance calculation’, Power Syst. Prot. Control, 2008, 36, (18), pp. 3742.
    34. 34)
      • 34. Xiang-Ning, L., Pei, L., Shi-Ming, L., et al: ‘A novel integrated morphology wavelet filter algorithm used for ultra-high speed protection of power systems’, Proc. CSEE, 2002, 22, (9), pp. 1924.
    35. 35)
      • 35. Jiandong, D., Baohui, Z., Jinfeng, R., et al: ‘Single-ended transient-based protection for EHV transmission lines basic theory’, Proc. CSEE, 2007, 27, (1), pp. 3743.
    36. 36)
      • 36. Parikh, U.B., Das, B., Maheshwari, R.P.: ‘Combined wavelet-SVM technique for fault zone detection in a series compensated transmission line’, IEEE Trans. Power Deliv., 2008, 23, (4), pp. 17891794.
    37. 37)
      • 37. ‘Steve R. Gunn, SVM Toolbox’, http://www.isis.ecs.soton.ac.uk/resources/svminfo/.
    38. 38)
      • 38. Chen, P.-Y., Lai, Y.-C., Zheng, J.-Y.: ‘Hardware design and implementation for empirical mode decomposition’, IEEE Trans. Ind. Electron., 2016, 63, (6), pp. 36863694.
    39. 39)
      • 39. Hong, Y.-Y., Bao, Y.-Q.: ‘FPGA implementation for real-time empirical mode decomposition’, IEEE Trans. Instrum. Meas., 2012, 61, (12), pp. 31753184.
    40. 40)
      • 40. Arafa, A.A., Saleh, H.I.: ‘A real-time scintillation crystal identification method and ITS FPGA implementation’, IEEE Trans. Nucl. Sci., 2014, 61, (5), pp. 24392445.
    41. 41)
      • 41. Kyrkou, C., Theocharides, T.: ‘A parallel hardware architecture for real-time object detection with support vector machines’, IEEE Trans. Comput., 2012, 61, (6), pp. 831842.
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