Regression tree for stability margin prediction using synchrophasor measurements

IEEE Transactions on Power Systems

Volumn 28, Issue 2, 2013, Pages 1978-1987

  Zheng, Ce ^a   Malbasa, Vuk ^a   Kezunovic, Mladen ^a  

^a Texas AandM University   (United States)

Author keywords

Decision trees; Phasor measurement units; Power system stability; Regression analysis

Indexed keywords

CONTINUATION POWER FLOW; OPTIMAL PLACEMENTS; PHASOR MEASUREMENT UNIT (PMUS); POWER SYSTEM STABILITY; STABILITY MARGINS; SYNCHROPHASOR MEASUREMENTS; TREE-BASED APPROACH; VOLTAGE COLLAPSE POINT;

DECISION TREES; ELECTRIC POWER SYSTEM INTERCONNECTION; FORESTRY; KNOWLEDGE BASED SYSTEMS; MODAL ANALYSIS; REGRESSION ANALYSIS; SYSTEM STABILITY;

PHASOR MEASUREMENT UNITS;

ERRORS; FORESTRY; MEASUREMENT; REGRESSION ANALYSIS;

EID: 84886402237     PISSN: 08858950     EISSN: None     Source Type: Journal    
DOI: 10.1109/TPWRS.2012.2220988     Document Type: Article

References (28)

1. L. Breiman, J. Friedman, R. A. Olshen, and C. J. Stone, Classificationand Regression Trees. Pacific Grove, CA: Wadsworth, 1984.
2. L. Wehenkel, T. V. Cutsem, and M. Ribbens-Pavella, "An artificialintelligence framework for on-line transient stability assessment ofpower systems," IEEE Trans. Power Syst., vol. 4, no. 2, pp. 789-800,May 1989.
3. L. Wehenkel, M. Pavella, E. Euxibie, and B. Heilronn, "Decision treebased transient stabilitymethod a case study," IEEE Trans. Power Syst.,vol. 9, no. 1, pp. 459-469, Feb. 1994.
4. S. Rovnyak, S. Kretsinger, J. Thorp, and D. Brown, "Decision trees forreal-time transient stability prediction," IEEE Trans. Power Syst., vol.9, no. 3, pp. 1417-1426, Aug. 1994.
5. K. Sun, S. Likhate, V. Vittal, V. S. Kolluri, and S. Mandal, "An onlinedynamic security assessment scheme using phasor measurements anddecision trees," IEEE Trans. Power Syst., vol. 9, no. 1, pp. 459-469,Feb. 2007.
6. T. V. Cutsem, L. Wehenkel, M. Pavella, B. Heilbronn, and M. Goubin,"Decision tree approaches to voltage security assessment," Proc. Inst.Elect. Eng., vol. 140, no. 3, pp. 189-198, May 1993.
7. R. Diao et al., "Decision tree-based online voltage security assessmentusing PMU measurements," IEEE Trans. Power Syst., vol. 24, no. 2,pp. 832-839, May 2009.
8. I. Kamwa, S. R. Samantaray, andG. Joos, "Catastrophe predictors fromensemble decision-tree learning of wide-area severity indices," IEEETrans. Smart Grid, vol. 1, no. 2, pp. 144-158, Sep. 2010.
9. R. F. Nuqui, A. G. Phadke, R. P. Schulz, and N. Bhatt, "Fast on-linevoltage security monitoring using synchronized phasor measurementsand decision trees," in Proc. IEEE Power Engineering Society WinterMeeting, 2001, vol. 3, pp. 1347-1352.
10. R. Diao, V. Vittal, and N. Logic, "Design of a real-time security assessmenttool for situational awareness enhancement in modern powersystems," IEEE Trans. Power Syst., vol. 25, no. 2, pp. 957-965, May 2010.
11. S. P. Teeuwsen, I. Erlich, M. A. El-Sharkawi, and U. Bachmann, "Genetic algorithm and decision tree-based oscillatory stability assessment,"IEEE Trans. Power Syst., vol. 21, no. 2, pp. 746-753, May2006.
12. L. Bruno and V. Ajjarapu, "Development of multi-linear regressionmodels for online voltage stability margin estimation," IEEE Trans.Power Syst., vol. 26, no. 1, pp. 374-383, Feb. 2011.
13. D. Q. Zhou, U. D. Annakkage, and A. D. Rajapakse, "Online monitoringof voltage stability margin using an artificial neural network,"IEEE Trans. Power Syst., vol. 25, no. 3, pp. 1566-1574, Aug. 2010.
14. F. R. Gomez, A. D. Rajapakse, U. D. Annakkage, and I. T. Fernando,"Support vector machine-based algorithm for post-fault transientstability status prediction using synchronized measurements," IEEETrans. Power Syst., vol. 26, no. 3, pp. 1474-1483, Aug. 2011.
15. I. Kamwa, S. R. Samantaray, and G. Joos, "Development of rule-basedclassifiers for rapid stability assessment of wide-area post-disturbancerecords," IEEE Trans. Power Syst., vol. 24, no. 1, pp. 258-270, Feb.2009.
16. I. Kamwa, S. R. Samantaray, and G. Joos, "On the accuracy versustransparency trade-off of data-mining models for fast-response PMU-basedcatastrophe predictors," IEEE Trans. Smart Grid, vol. 3, no. 1,pp. 152-161, 2012.
17. T. Van Cutsem and C. Vournas, Voltage Stability of Electric Power Systems. Boston, MA: Kluwer, 1998.
18. P. Kundur et al., "Definition and classification of power system stabilityIEEE/CIGRE joint task force on stability terms and definitions, "IEEE Trans. Power Syst., vol. 19, no. 3, pp. 1387-1401, Aug. 2004.
19. V. Ajjarapu and C. Christy, "The continuation power flow: A tool forsteady state voltage stability analysis," IEEE Trans. Power Syst., vol.7, no. 1, pp. 416-423, Feb. 1992.
20. S. Dan and M. Golovnya, CART 6.0 User's Manual. San Diego, CA:Salford Systems, 2006.
21. P. M. Anderson and A. A. Fouad, Power System Control and Stability. Ames, IA: The Iowa State Univ. Press, 1977, p. 38.
22. M. A. Pai, Energy Function Analysis for Power System Stability.Boston, MA: Kluwer, 1989.
23. Y. Zhou and V. Ajjarapu, "A fast algorithm for identification andtracing of voltage and oscillatory stability margin boundaries," Proc.IEEE, vol. 93, no. 5, pp. 934-946, May 2005.
24. R. G. D. Steel and J. H. Torrie, Principles and Procedures of Statistics.New York: McGraw-Hill, 1960.
25. R. F. Nau, Forecasting, Feb. 2005. [Online]. Available: http://www.duke.edu/~rnau/rsquared.htm.
26. Electric Power Research Institute, DC Multi-Infeed Study, EPRITR-104586s, Projects 2675-04-05, Final Report, 1994.
27. IEEE Standard for Synchrophasors for Power Systems, IEEE Std. C37.118-2005, 2005.
28. Y. Yang, X. Wu, and X. Zhu, "Mining in anticipation for conceptchange: Proactive-reactive prediction in data streams," Data MiningKnowl. Discov., no. 13, pp. 261-289, 2006.