Detection and Analysis of Power Quality Issues in Railway Traction System using Fuzzy Based Wavelet Transform

The electric traction system uses the electrical power network to supply the locomotive. The railway traction load being a single-phase load, 3-phase power at the substation requires to be transformed to two single-phase systems. One phase is connected to the traction load while the other is connected to the auxiliary load. Thus, the loads in these two phases are rarely balanced. Extensive usage of power electronic converters to cater to the need of different power levels for traction load, and the dynamic and nonlinear characteristics of traction load cause power quality (PQ) issues. These power quality issues include total harmonic distortions (THD), voltage and current unbalance, voltage sag, flicker, notches etc. As the load balance degree declines, the imbalance in the supply side current rises. This work first focuses on the modelling of traction load and then analyzes the power quality issues at the “point of common coupling” (PCC) in electric railway traction power supply systems through a simulation study on the basis of data collected from traction substation. Power quality analysis is carried out using wavelet transform for different mother wavelets, orders, levels, and thresholding techniques. The work proposes a wavelet transform-based fuzzy expert system to analyze and enhance the power quality of the traction system.