Transmission Line Fault Location Using PCA-Based Best-Fit Curve Analysis

Abstract

The paper presents a principal component analysis (PCA)-based method for localization of various power system faults in a 150 km long single side fed transmission line using quarter-cycle pre-fault and half-cycle post-fault sending end line current signals. The proposed work uses fault signals of ten different types of seven intermediate locations along the length of the line to develop three-phase PCA score indices. The localizer model is also designed for practical fitment, with fault signals contaminated with power system noise. These seven sets of indices are further used with the best-fit curve fitting method in the MATLAB environment to develop fault curves. Minimum root mean square error criteria are followed for selecting the fit type. Each fault class is designed with the required number of curves to estimate fault location. The proposed work produces a highly accurate localization, with only 0.1271% average percentage error for fault localization, and a maximum percentage error of 0.5821% for the 150 km line.