Support vector machine-based algorithm for post-fault transient stability status prediction using synchronized measurements

IEEE Transactions on Power Systems

Volumn 26, Issue 3, 2011, Pages 1474-1483

  Gomez, Francisco R ^a   Rajapakse, Athula D ^a   Annakkage, Udaya D ^a   Fernando, Ioni T ^b  

^a UNIVERSITY OF MANITOBA   (Canada)

^b MANITOBA HYDRO   (Canada)

Author keywords

Nonlinear classifiers; phasor measurement units; support vector machines; transient stability; wide area protection and control

Indexed keywords

ACCURATE PREDICTION; BALANCED AND UNBALANCED FAULT; LARGE DISTURBANCE; MACHINE-BASED ALGORITHM; NETWORK TOPOLOGY; NEW ENGLAND; NONLINEAR CLASSIFIERS; OPERATING CONDITION; PHASOR MEASUREMENT UNIT; POWER NETWORKS; RECOVERY VOLTAGE; ROTOR ANGLE; SAMPLED VALUES; SENSITIVE LOADS; SUPPORT VECTOR; SYNCHRONIZED MEASUREMENT; TEST SYSTEMS; TRANSIENT INSTABILITY; TRANSIENT STABILITY PREDICTION; VOLTAGE MAGNITUDE; WIDE AREA PROTECTION AND CONTROL;

ALGORITHMS; ELECTRIC EQUIPMENT PROTECTION; ELECTRIC NETWORK ANALYSIS; ELECTRIC NETWORK TOPOLOGY; ELECTRIC POWER SYSTEM INTERCONNECTION; FORECASTING; MEASUREMENT ERRORS; PHASE MEASUREMENT; POWER TRANSMISSION; STABILITY; SUPPORT VECTOR MACHINES; UNITS OF MEASUREMENT; WIDE AREA NETWORKS;

POWER QUALITY;

EID: 79960889557     PISSN: 08858950     EISSN: None     Source Type: Journal    
DOI: 10.1109/TPWRS.2010.2082575     Document Type: Article

References (37)

1. D. Karlsson and S. Lindahl, "Wide area protection and emergency control," in Proc. IEEE Power Eng. Soc. General Meeting, 2004, vol. 1, p. 5.
2. F. F. Song, T. S. Bi, and Q. X. Yang, "Study on wide area measurement system based transient stability control for power systems," in Proc. IPEC Power Engineering Conf., 2005, vol. 2, pp. 757-760.
3. A. G. Phadke, "Synchronized phasor measurements in power systems," IEEE Comput. Appl. Power, vol. 6, no. 2, pp. 10-15, Apr. 1993. (Pubitemid 23638773)
4. H. Dongchen and V. Venkatasubramanian, "New wide-area algorithms for detection and mitigation of angle instability using synchrophasors," in Proc. Power Eng. Soc. General Meeting, 2007, pp. 1-8.
5. P. M. Anderson and A. A. Fouad, Power System Control and Stability, 2nd ed. Piscataway, NJ: IEEE, 2003.
6. P. Kundur, N. J. Balu, and M. G. Lauby, Power System Stability and Control. New York: McGraw-Hill, 1994.
7. M. A. Pai, Energy Function Analysis for Power System Stability. Boston, MA: Kluwer, 1989.
8. D. Ruiz-Vega and M. Pavella, "A comprehensive approach to transient stability control. I. Near optimal preventive control," IEEE Trans. Power Syst., vol. 18, no. 4, pp. 1446-1453, Nov. 2003.
9. Y. Xue, L.Wehenkel, R. Belhomme, P. Rousseaux, M. Pavella, E. Euxibie, B. Heilbronn, and J. F. Lesigne, "Extended equal area criterion revisited (EHV power systems)," IEEE Trans. Power Syst., vol. 7, no. 3, pp. 1012-1022, Aug. 1992. (Pubitemid 23563467)
10. M. Pavella, D. Ernst, and D. Ruiz-Vega, Transient Stability of Power Systems : A Unified Approach to Assessment and Control. Boston, MA: Kluwer, 2000.
11. L.Wehenkel, T. van Cutsem, and M. Ribbens-Pavella, "An artificial intelligence framework for on-line transient stability assessment of power systems," IEEE Power Eng. Rev., vol. 9, no. 5, pp. 77-78, May 1989.
12. L.Wehenkel, M. Pavella, E. Euxibie, and B. Heilbronn, "Decision tree based transient stability method a case study," IEEE Trans. Power Syst., vol. 9, no. 1, pp. 459-469, Feb. 1994.
13. D. J. Sobajic and Y.-H. Pao, "Artificial neural-net based dynamic security assessment for electric power systems," IEEE Power Eng. Rev., vol. 9, no. 1, p. 55, Feb. 1989.
14. S. Rovnyak, S. Kretsinger, J. Thorp, and D. Brown, "Decision trees for real-time transient stability prediction," IEEE Trans. Power Syst., vol. 9, no. 3, pp. 1417-1426, Aug. 1994.
15. Z. Qin, J. Davidson, and A. A. Fouad, "Application of artificial neural networks in power system security and vulnerability assessment," IEEE Trans. Power Syst., vol. 9, no. 1, pp. 525-532, Feb. 1994.
16. L. S. Moulin, A. P. A. da Silva, M. A. El-Sharkawi, and R. J. Marks, II, "Support vector machines for transient stability analysis of large-scale power systems," IEEE Trans. Power Syst., vol. 19, no. 2, pp. 818-825, May 2004.
17. C. Jensen, M. El-Sharkawi, and R. Marks, "Power system security assessment using neural networks: Feature selection using fisher discrimination," IEEE Power Eng. Rev., vol. 21, no. 4, p. 62, Nov. 2001.
18. A. E. Gavoyiannis, D. G. Vogiatzis, D. R. Georgiadis, and N. D. Hatziargyriou, "Combined support vector classifiers using fuzzy clustering for dynamic security assessment," in Proc. IEEE Power Eng. Soc. Summer Meeting, 2001, vol. 2, pp. 1281-1286.
19. S. Kai, S. Likhate, V. Vittal, V. S. Kolluri, and S. Mandal, "An online dynamic security assessment scheme using phasor measurements and decision trees," IEEE Trans. Power Syst., vol. 22, no. 4, pp. 1935-1943, Nov. 2007. (Pubitemid 350141994)
20. I. Kamwa, S. R. Samantaray, and G. Joos, "Development of rule-based classifiers for rapid stability assessment of wide-area post-disturbance records," IEEE Trans. Power Syst., vol. 24, no. 1, pp. 258-270, Feb. 2009.
21. A. D. Rajapakse, F. R. Gomez, K. Nanayakkara, P. A. Crossley, and V. T. Terzija, "Rotor angle instability prediction using post-disturbance voltage trajectories," IEEE Trans. Power Systems, vol. 25, no. 2, pp. 947-956, May 2010.
22. S. M. Rovnyak, C. W. Taylor, and Y. Sheng, "Decision trees using apparent resistance to detect impending loss of synchronism," IEEE Trans. Power Del., vol. 15, no. 4, pp. 1157-1162, Oct. 2000. (Pubitemid 32252106)
23. C. J. C. Burges, A Tutorial on Support Vector Machines for Pattern Recognition. Norwell, MA: Kluwer, 1998.
24. N. Cristianini and J. Shawe, An Introduction to Support Vector Machines. Cambridge, U.K.: Cambridge Univ. Press, 2000.
25. V. S. Cherkassky and F. Mulier, Learning From Data: Concepts, Theory, and Methods, 2nd ed. Hoboken, NJ: IEEE Press: Wiley-Interscience, 2007.
26. P. W. Sauer and M. A. Pai, Power System Dynamics and Stability. Englewood Cliffs: Prentice-Hall, 1997.
27. A. G. Phadke and J. S. Thorp, Synchronized Phasor Measurements and Their Applications. New York: Springer, 2008.
28. E. E. Osuna, "Support vector machines: Training and applications," Ph.D. dissertation, Massachusetts Inst. Technol., Sloan Sch. Manage., Cambridge, MA, 1998.
29. "TSAT (Transient Security Assessment Tool) Manual," Powertech Labs Inc., 2004.
30. V. Kecman, Learning and Soft Computing: Support Vector Machines, Neural Networks, and Fuzzy Logic Models. Cambridge, MA: MIT Press, 2001.
31. X. Qing-Qiang, J. Suonan, and G. Yao-Zhong, "Real-time measurement of mean frequency in two-Machine system during power swings," IEEE Trans. Power Del., vol. 19, no. 3, pp. 1018-1023, Jul. 2004.
32. IEEE Standard for Synchrophasors for Power Systems, IEEE Std. C37. 118-2005 (Revision of IEEE Std. 1344-1995), 2006.
33. W. Hongbin, C. Hsiao-Dong, and C. Byoung-Kon, "Slow voltage recovery response of several load models: Evaluation study," in Proc. 2008 IEEE Power and Energy Soc. General Meeting-Conversion and Delivery of Electrical Energy in the 21st Century, 2008, pp. 1-6.
34. IEEE Task Force on Load Representation for Dynamic Performance, USA, "Load representation for dynamic performance analysis (of power systems)," IEEE Trans. Power Syst., vol. 8, no. 2, pp. 472-482, May 1993.
35. S. P. T. I. PTI. 2007, PSS/E Program Operation Manual.
36. P. S. Srinivasareddy, L. Ramesh, S. P. Chowdhury, and S. Chowdhury, "Power system PMU placement-a comparative survey report," in Proc. IET-UK Int. Conf. Information and Communication Technology in Electrical Sciences (ICTES 2007), 2007, pp. 249-255.
37. I. Kamwa and R. Grondin, "PMU configuration for system dynamic performance measurement in large multi-area power systems," in Proc. 2002 IEEE Power Eng. Soc. Summer Meeting, 2002, vol. 1, p. 239.