Approach for High voltage transmission line protection by using line trap network & ANN over SVM

  Aaditya P.Agarkar,  Dr.Swapnil B.Mohod

This paper presents a new approach to classify fault types and predict the fault location in the high-voltage power transmission lines, by using ANN over Support Vector Machines (SVM) and Wavelet Transform (WT) of the measured one-terminal voltage and current transient signals. Wavelet entropy criterion is applied to wavelet detail coefficients to reduce the size of feature vector before classification and prediction stages. The experiments performed for different kinds of faults occurred on the transmission line have proved very good accuracy of the proposed fault location algorithm. The fault classification error is below 1% for all tested fault conditions. Efficiency of this method is 89% as compared with Support vector machine technique having 73% efficiency and the maximum error did not exceed 0.95 km.

Keywords- Line trap, support vector machine (svm), transients-based protection, Matlab

Unique Identification Number - IJEDR1703039
Page Number(s) - 254-262
Pubished in - Volume 5 | Issue 3 | July 2017
DOI (Digital Object Identifier) -   
Publisher - IJEDR (ISSN - 2321-9939)

  Aaditya P.Agarkar,  Dr.Swapnil B.Mohod,   "Approach for High voltage transmission line protection by using line trap network & ANN over SVM", International Journal of Engineering Development and Research (IJEDR), ISSN:2321-9939, Volume.5, Issue 3, pp.254-262, July 2017, Available at :http://www.ijedr.org/papers/IJEDR1703039.pdf