Wavelet Analysis of the Fault Transient Phenomena on an Improved Thyristor Controlled Series Compensated Transmission Line Model with Particular Reference to Fault Type Classification

In this paper, a novel approach to analyse, extract and validate the key characteristics of the fault transient phenomena on a thyristor controlled series capacitor (TCSC) compensated transmission line is introduced. This method relies on utilising discrete wavelet transform (DWT) to decompose the traditional busbar voltages and line currents obtained from a single terminal into a series of time-scale representation. A feature modelling using Self-Organising Maps (SOM) is then applied to verify the classification capability of the extracted features. This is of paramount importance to the successful development of the subsequent artificial neural network (ANN) based fault type classifier for TCSC-compensated lines particularly since the closed-loop current control (CLCC) mode of the TCSC, which attenuates the performance of the fault type classifier developed hitherto, is considered herein. Validation data showing the potential of these techniques for feature extraction of the simulated TCSC fault transients in Kayenta substation (USA) is also presented.