Recently, power distribution system is getting larger and more complex. It is very difficult even for the experts to diagnosis and monitoring to made best action. This motivated many researchers to investigate power systems in an effort to improve reliability by focusing on fault detection and classification. There have been many studies on problems but the results are not good enough for applying to real power system. In this paper, a new protective relaying framework to diagnosis and monitoring faults in an electrical power distribution system with. This work will extract fault signatures by using ellipse fit using least squares criterion during fault condition. By utilizing principal component analysis methods, this system will identify, classify and localize any fault instantaneously.
References
[1]
P. Raval, “ANN Based Classification and Location of Faults in EHV Transmission Line,” Proceedings of the International Multi-Conference of Engineers and Computer Scientists, Hong Kong, 19-21 March 2008, pp.
[2]
Z. Q. Bo, R. K. Aggarwal, A. T. Johns, H. Y. Li and Y. H. Song, “A New Approach to Phase Selection Using Fault Generated Frequency Noise and Neural Networks,” IEEE Transactions on Power Delivery, Vol. 12, No. 1, 1997, pp 106-113. doi:10.1109/61.568230
[3]
M. Hagh, K. Razi and H. Taghizadeh, “Fault Classification and Location of Power Transmission Lines Using Artificial Neural Network,” International Power Engineering Conference, Singapore, 3-6 December 2007, pp. 1109-1114.
[4]
H. Hizam and P. Crossley, “Single-Ended Fault Location Technique on a Radial Distribution Network Using Fault Generated Current Signals,” Seminar on Engineering and Technology, Putrajaya, 2006, pp. 148-158.
[5]
F. Magnago and A. Abur, “Fault Location Using Wavelets,” IEEE Transactions on Power Delivery, Vol. 13, No. 4, 1998, pp. 1475-1480.
[6]
M. B. de Sousa and A. K. Barros, “Fault Location in Medium and High Voltage Transmission Line through Efficient Coding,” IEEE/PES Transmission and Distribution Conference and Exhibition, Dallas, 21-24 May 2006, pp. 893-898.
[7]
J. Liang, S. Elangovan and J. B. X. Devotta, “A Wavelet Multire Solution Analysis Approach to Fault Detection and Classification in Transmission Lines,” Electrical Power and Energy Systems, Vol. 20, No. 5, 1998, pp. 327-332.
doi:10.1016/S0142-0615(97)00076-8
[8]
D. Chanda, N. K. Kishore and A. K. Sinha, “Application of Wavelet Multire Solution Analysis for Identification and Classification of Faults on Transmission Lines,” Electric Power Systems Research, Vol. 73, No. 3, 2005, pp. 323-333. doi:10.1016/j.epsr.2004.07.006
[9]
Q. Alsafasfeh, I. Abdel-Qader and A. Harb, “Symmetrical Pattern and PCA Based Framework for Fault Detection and Classification in Power System,” Proceedings of IEEE Electro/Information Technology Conference, Normal, May 2010, pp. 1-5.
[10]
J. Sadeh and H. Afradi, “A New and Accurate Fault Location Algorithm for Combined Transmission Lines Using Adaptive Network-Based Fuzzy Inference System,” Electrical Power Systems Research, Vol. 79, No. 11, 2009, pp. 1538-1545.
