Accurate Fault Classification and Section Identification Scheme in TCSC Compensated Transmission Line using SVM
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 32799
Accurate Fault Classification and Section Identification Scheme in TCSC Compensated Transmission Line using SVM

Authors: Pushkar Tripathi, Abhishek Sharma, G. N. Pillai, Indira Gupta

Abstract:

This paper presents a new approach for the protection of Thyristor-Controlled Series Compensator (TCSC) line using Support Vector Machine (SVM). One SVM is trained for fault classification and another for section identification. This method use three phase current measurement that results in better speed and accuracy than other SVM based methods which used single phase current measurement. This makes it suitable for real-time protection. The method was tested on 10,000 data instances with a very wide variation in system conditions such as compensation level, source impedance, location of fault, fault inception angle, load angle at source bus and fault resistance. The proposed method requires only local current measurement.

Keywords: Fault Classification, Section Identification, Feature Selection, Support Vector Machine (SVM), Thyristor-Controlled Series Compensator (TCSC)

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1078491

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2450

References:


[1] R. M. Mathur, and R. K. Varma, Thyristor-Based Facts Controllers for Electrical Transmission Systems, John Wiley & Sons, inc. Publication, 2002.
[2] Q Y Xuan and A T Johns. "Digital simulation of series-compensated EHV (extra high voltage) Transmission systems" in Simulation of Power Systems, IEE Colloquium on, dec 1992, pp. 1-3.
[3] "Single phase tripping and auto reclosing of transmission lines-ieee committee report," Power Delivery, IEEE Transactions on,vol. 7, no 1, pp. 182-192, jan 1992.
[4] D. Thomas and C. Christopoulos, "Ultra-High Speed Protection of Series Compensated Lines", Power Delivery, IEEE Transactions on,vol. 7, no 1, pp. 139-145, jan 1992.
[5] A. Girgis, A. Sallam, A. El-Din, "An Adaptive Protection Scheme for Advanced Series Compensated (ASC) Transmission Lines", Power Delivery, IEEE Transactions on,vol. 13, no. 2, pp. 414-420, April 1998.
[6] W. Cheong and R. Agrawal, "A Novel Feature Extraction and Optimization Method for Neural Network-based Fault Classification in TCSC-Compensated Lines", Power Engineering Society Summer Meeting, 2002 IEEE, vol. 2, july 2002 2002, pp. 795-800.
[7] Q. Y. Xuan, Y. H. Song, A. T. Johns, R. Morgan and D. Williams, "Performance of an adaptive protection scheme for series compensated EHV transmission systems using neural networks", Electric Power System Research., Vol. 36, no. 1, pp. 57-66, January 1996.
[8] Y. H. Song, A. T. Johns, Q. Y. Xuan, "Radial Basis Function Neural Networks for fault Diagnosis in Controllable Series Compensated Transmission Lines", Electro-technical conference- MELECON '96, 8th Mediterranean, Vol. 3, May 1996, pp. 13-16.
[9] A. K. Pradhan, A. Routray, S. Pati, and D. K. Pradhan, " Wavelet Fuzzy Combined Approach for Fault Classification of a Series-Compensated Transmission Line", Power Delivery, IEEE Transactions on, Vol. 19, no. 4, October 2004, pp. 1612-1618.
[10] A. K. Pradhan, A. Routrsy, and B. Biswal, "Higher Order Statistics- Fuzzy Integrated Scheme for Fault Classification of a Series Compensated Transmission Line", Power Delivery, IEEE Transactions on, Vol. 19, April 2004, pp. 891-893.
[11] B. Das, J.V.Reddy, "Fuzzy-logic-based fault classification scheme for digital distance protection", Power Delivery, IEEE Transactions on, Vol. 20, April 2005, pp.609-616.
[12] Bhalja, Bhavesh and Maheshwari, R. P., "Wavelet-based fault classification scheme for a transmission line using a support vector machine", Electric Power Component and System, Vol. 36, no. 10, 2008, pp.1017-1030.
[13] Dash P. K., Samantaray, S. R.; Panda, G., "Fault Classification and Section Identification of an Advanced Series-Compensated Transmission Line Using Support Vector Machine", Power Delivery, IEEE Transactions on, Vol. 22, no. 1, January 2007, pp. 67-73.
[14] U. B. Parikh, B. Das, R. Maheshwari, "Fault classification technique for series compensated transmission line using support vector machine", International Journal of Electrical Power & Energy Systems, Vol. 32, no. 6, July 201, pp. 629-636.
[15] Gangadharan R., Pillai G.N., Gupta I., "Fault zone detection on advanced series compensated transmission line using discrete wavelet transform and SVM", Proceedings of World Academy of Science, Engineering andTechnology, vol. 70, 2010, pp. 176-180.
[16] H. Simon, NEURAL NETWORKS: A Comprehensive Foundatio, 2nd Ed., Printice-Hall, Inc., 1999.
[17] C. M. Bishop, Pattern Recognition and Machine Learning, Springer, 2006.
[18] PSCAD/EMTDC v 4.2.0, Manitoba HVDC Research center.
[19] V. Vapnik, "An Overview of Statistical Learning Theory," Neural Networks, IEEE Transaction on, vol. 10, no. 5, September 1999, pp. 988-999.
[20] C. Cortes, and V. Vapnik, "Support Vector Networks", Machine Learning, Vol. 20, 1995, pp. 273-297.
[21] C. W. Hsu and C. J. Lin, "A Comparison of Methods for Multiclass Support Vector Machines", Neural Networks, IEEE Transaction on, vol. 13, no. 2, March 2002, pp. 415- 425.
[22] C. C. Chang and C. J. Lin, "LIBSVM: A library for support vector machines", ACM Transactions on Intelligent Systems and Technology, vol. 2, 2011, pp. 1-27, Software available at http://www.csie.ntu.edu.tw/ ~cjlin/libsvm.
[23] Y.H. Song, A.T. Johns, Q.Y. Xuan, "Artificial neural-network-based protection scheme for controllable series-compensated EHV transmission lines", Generation, Transmission and Distribution, IEE Proceedings, Vol. 143, no. 6, November 1996, pp. 535- 540.