An improved fault-location method for distribution system using wavelets and support vector regression

This paper presents a wavelets and support vector regression (SVR) based method for locating grounded faults in radial distribution systems. The method utilizes traveling wave data recorded at the substation only. After modal transformation on three-phase traveling waves, the arrival time and amplitude information of modal components are extracted using discrete wavelet transform (DWT). In particular, time delay and ratio between the first Wavelet Transform Modulus Maxima (WTMM) of modal components in each scale are the candidate features for training a SVR which will be used for fault distance prediction. The simulation and SVR process are performed respectively using PSCAD/EMTDC and MATLAB. The result shows the method has high accuracy and good stability.