Statistical decision-tree based fault classification scheme for protection of power transmission lines

• Published in: International journal of electrical power & energy systems 2012-03, Vol.36 (1), p.1-12
• Main Authors: Upendar, J., Gupta, C.P., Singh, G.K.
• Format: Article
• Language: English
• Subjects: Algorithms; Applied sciences; Artificial neural network (ANN); Carts; Classification; Classification and Regression Tree method (CART); Computer simulation; Electrical engineering. Electrical power engineering; Electrical power engineering; Exact sciences and technology; Fault classification; Faults; Matlab; Miscellaneous; Power networks and lines; Statistical methods; Testing. Reliability. Quality control; Transmission lines; Wavelet transforms; Wavelets
• ISSN: 0142-0615; 1879-3517
• DOI: 10.1016/j.ijepes.2011.08.005

This paper presents a statistical algorithm for classification of faults on power transmission lines. The proposed algorithm is based upon the wavelet transform of three phase currents measured at the sending end of a line and the Classification and Regression Tree (CART) method, a commonly available statistical method. Wavelet transform of current signal provides hidden information of a fault situation as an input to CART algorithm, which is used to classify different types of faults. The proposed technique is simulated using MATLAB/SIMULINK software and it is tested upon the data created with the fault analysis of the 400 kV sample transmission line considering wide variations in the operating conditions. The classification results are also compared with the results obtained using back propagation neural network.