Synchrophasor Assisted Fault Diagnosis using Support Vector Machine

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P. Paavani
S. N. Singh
S. C. Srivastava

Abstract

This paper presents a Support Vector Machine (SVM) based fault detection, classifi cation and location using synchrophasor measurements obtained from the optimally placed Phasor Measurement Units (PMUs) for ensuring fault observability. An Integer Linear Programming (ILP) based PMU placement method is proposed, considering the minimization of installation cost as objective with line observability as its constraint. The breaker and half bus-bars scheme is considered at one of the substations to show its impact on the Optimal PMUs Placement (OPP). After the OPP, a SVM based post-fault studies are carried out using the synchrophasor measurements, available from the PMUs. Three types of SVM-Classifi ers (SVM-C) are used for the fault detection, faulted line identifi cation and the fault classifi cation. Further, fault location is carried out using Support Vector Regressor (SVR) in which four SVMs are utilized, one for each fault type. The same classifi cation and regression is carried out using Radial Basis Neural Networks (RBFNNs) and the results obtained from SVM are compared. The performance of the proposed method is studied on WSCC-9 bus system with and without consideration of the breaker and half bus-bar scheme and on New England (NE)-39 bus system.

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How to Cite
Paavani, P., Singh, S. N., & Srivastava, S. C. (2011). Synchrophasor Assisted Fault Diagnosis using Support Vector Machine. Power Research - A Journal of CPRI, 187–198. Retrieved from https://cprijournal.in/index.php/pr/article/view/940

References

  1. Vapnik V. “Statistical learning theory”, Wiley, New York, 1998.
  2. Phadke A G and Thorp J S. “Synchronized phasor measurements and their applications”, Springer, New York, 2008.
  3. Ali Abur and Antonio Gómez Expósito. “Power system state estimation: Theory and Implementation”, CRC Press, March 24th 2004.
  4. Articles in Journals
  5. Saikat Chakrabarti and Elias Kyriakides. “Optimal placement of phasor measurement units for power system observability”, IEEE, Transactions on Power Systems, Vol. 23, No. 3, pp. 1433–1440, August 2008.
  6. Kai-Ping Lien, Chih-Wen Liu, Chi-Shan Yu and Joe-Air Jiang. “Transmission network fault location observability with minimal PMU placement”, IEEE, Transactions on Power Delivery, Vol. 21, No. 3, pp. 1128–1136, July 2006.
  7. Exposito A and Abur A. “Generalized observability analysis and measurement classifi cation”, IEEE, Transactions on Power Systems, Vol. 13, No. 3, pp. 1090–1095, August 1998.
  8. Baldwin T L, Mili L, Boisen M B and Jr. Adapa R. “Power system observability with minimal phasor measurement placement”, IEEE, Transactions on Power Systems, Vol. 8, No. 2, pp. 707–715, May 1993.
  9. Ravikumar B, Thukaram D and Khincha H P. “Application of support vector machine for fault diagnosis in power transmission system,” IET, Gener. Transm. Distrib.,Vol. 2, No. 1, pp. 119–130 January 2008.
  10. Devesh Dua, Sanjay Dambhare, Rajeev Kumar Gajbhiye and Soman S A. “Optimal multi stage scheduling of PMU placement: An ILP approach”, IEEE, Transactions on Power Delivery, Vol. 23, No. 4, pp. 1812–1820, October 2008.
  11. Nuqui R F and Phadke A G. “Phasor measurement unit placement techniques for complete and incomplete observability”, IEEE, Transactions on Power Delivery, Vol. 20, No. 4, pp. 2381–2388, October 2005.
  12. Abur A and Magnago F H. “Optimal meter placement for maintaining observability during single branch outage”, IEEE, Transactions on Power Systems, Vol. 14, No. 4, pp. 1273–1278, November 1999. Conferences and Reports
  13. Ranjana Sodhi, Srivastava S C and Singh S N. “Optimal PMU placement to ensure system observability under contingencies”, IEEE, PES General Meeting, pp. 1–6, July 2009.
  14. Xu B and Abur A. “Observability analysis and measurement placement for systems with PMUs”, IEEE, Power Systems Conference and Exposition, Vol. 2, pp. 943–946, 2004.
  15. Seethalekshmi K, Singh S N and Srivastava S C. “Wide-area protection and control: present status and key challenges”, Fifteenth National Power System Conference (NPSC), IIT, Bombay, pp.169–175, December 2008.
  16. Pei Zhang, “Phasor measurement unit implementation and applications”, EPRI Final Report, 2006.
  17. FAN Chunju, DU Xiuhua, LI Shengfang and YU Weiyong. “An adaptive fault location technique based on PMU on transmission line”, IEEE, Power and Energy Society GM, Pittsburg, Pennsylvania, USA, pp. 1–6, July 2007.
  18. Steve R Gunn. “Support vector machine for classifi cation and regression”, Technical report, May 10 1998.
  19. Weston J and Watkins C. “Multiclass support vector machine”, Technical report, 1998.
  20. Websites
  21. Chih-Wei Hsu, Chih-Chung Chang, and Chih-Jen Lin. “A practical guide to support vector machines”, Guide, 2010. http://www.csie.ntu.edu.tw/~cjlin/libsvm/