INFORMATION CHANGE THE WORLD

International Journal of Intelligent Systems and Applications(IJISA)

ISSN: 2074-904X (Print), ISSN: 2074-9058 (Online)

Published By: MECS Press

IJISA Vol.5, No.8, Jul. 2013

The Application of Phasor Measurement Units in Transmission Line Outage Detection Using Support Vector Machine

Full Text (PDF, 956KB), PP.9-20


Views:108   Downloads:0

Author(s)

A. Y. Abdelaziz, S. F. Mekhamer, M. Ezzat

Index Terms

Phasor Measurement Units, Support Vector Machine, Radial Basis Function Kernel

Abstract

Many protection applications are based upon the Phasor Measurement Units (PMUs) technology. Therefore, PMUs have been increasingly widespread throughout the power network, and there are several researches have been made to locate the PMUs for complete system observability. This paper introduces an important application of PMUs in power system protection which is the detection of single line outage. In addition, a detection of the out of service line is achieved depending on the variations of phase angles measured at the system buses where the PMUs are located. Hence, a protection scheme from unexpected overloading in the network that may lead to system collapse can be achieved. Such detections are based upon an artificial intelligence technique which is the support Vector Machine (SVM) classification tool. To demonstrate the effectiveness of the proposed approach, the algorithm is tested using offline simulation for both the 14-bus IEEE and the 30-bus IEEE systems. Two different kernels of the SVM are tested to select the more appropriate one (i.e. polynomial and Radial Basis Function (RBF) kernels are used).

Cite This Paper

A. Y. Abdelaziz, S. F. Mekhamer, M. Ezzat,"The Application of Phasor Measurement Units in Transmission Line Outage Detection Using Support Vector Machine", International Journal of Intelligent Systems and Applications(IJISA), vol.5, no.8, pp.9-20, 2013.DOI: 10.5815/ijisa.2013.08.02

Reference

[1]US-Canada Power System Outage Task Force. Final Report on August 14, 2003 the Blackout in the United States and Canada, 2004. 

[2]US-Canada Power System Outage Task Force. Final Report on the Implementation of the Task Force Recommendations, 2006.

[3]B. Singh, N. Sharma, A. Tiwari, K. Verma, and S. Singh, “Applications of phasor measurement units (PMUs) in electric power systems network incorporated with FACTS controllers,” International Journal of Engineering, Science and Technology, vol. 3, no. 3, pp. 64–82, 2011.

[4]Weiqing Jiang, Vijay Vittal, and Gerald T. Heydt, "A Distributed State Estimator Utilizing Synchronized Phasor Measurements", IEEE Transactions on Power Systems, Vol. 22, No. 2, pp. 563-571, May 2007.

[5]George N. Korres, and Nikolas M. Manousakis, "State estimation and bad data processing for system including PMU and SCADA measurements", Electric Power Systems Research, 81 (2011), pp. 1514-1524, March 2011.

[6]A. Monticelli, “Modeling circuit breakers in weighted least squares state estimation,” IEEE Trans. Power Syst., vol. 8, no. 3, pp. 1143–1149, Aug. 1993.

[7]M. Kezunovic, “Monitoring of power system topology in real-time,” in Proc. 39th Hawaii Int. Conf. System Sciences, Jan. 2006.

[8]E. Lourenço, A. Costa, K. Clements, and R. Cernev, “A topology error identification method directly based on collinearity tests,” IEEE Trans. Power Syst., vol. 21, no. 4, pp. 1920–1929, Nov. 2006.

[9]T. A. Mikolinnas and B. F. Wollenberg, “An advanced contingency selection algorithm,” IEEE Trans. Power Apparatus Syst., vol. PAS-100, no. 2, pp. 608–617, Feb. 1981.

[10]G. D. Irissari, and A. M. Sasson, “An automatic contingency selection method for online security analysis,” IEEE Trans Power Apparatus Syst., vol. PAS-100, no. 4, pp. 1838–1844, Apr. 1981.

[11]S. Vemuri, and R. E. Usher, “On line automatic contingency selection algorithms,” IEEE Trans Power Apparatus Syst., vol. PAS-102, no. 2, pp. 346–354, Feb. 1983.

[12]D. Hazarika, S. Bhuyan, and S.P. Chowdhury, “Line outage contingency analysis including the system islanding scenario” Electrical Power and Energy Systems, vol. 28, no. 4, pp, 232–243, May 2006.

[13]J. E. Tate, and T. J. Overbye, “Line outage detection using phasor angle measurements,” IEEE Transactions on Power Systems, vol. 23, no. 4, pp. 1644–1652, Nov. 2008.

[14]J. E. Tate, and T. J. Overbye, “Double line outage detection using phasor angle measurements,” IEEE Power & Energy Society General Meeting Proceeding, pp. 1–5, July 2009. 

[15]S. Chakrabarti, and E. Kyriakides, “Optimal placement of phasor measurement units for power system observability,” IEEE Transactions on Power Systems, vol. 23, no. 3, pp. 1433–1440, Aug. 2008.

[16]S. Abe, Support Vector Machines for Pattern Classification. England: Springer-Verlag, London, Ltd, 2005.

[17]I. Steinwart, and A. Christmann, Support Vector Machines, New York: Springer, 2008.

[18]V. Vapnik, “The Nature of Statistical Learning Theory,”. Springer, N.Y., 1995. ISBN 0-387-94559-8.

[19]Q. H. Wu, Z. Lu and T. Y. Ji, Protective relaying of power systems using mathematical Morophology, Springer-Verlag London Limited 2009.

[20]PSCAD User’s Guide Ver. 4.2, Manitoba Research Center, April 2005.