High impedance fault detection in EHV series compensated lines using the wavelet transform

Abstract

Coupling capacitive voltage transformers behave as low pass filters which reject the high frequencies associated with voltage signals, so the effect of HIF on voltage signals is neglected. In addition, using series capacitors (SCs) equipped with metal oxide varistors (MOVs) increases the protection relaying problems and complicates the trip decision. This paper presents a high impedance fault detection algorithm for maximum trip time required of 3/4 cycle. The proposed scheme implemented on two different models of HIF in extra high voltage double-ended transmission lines with series capacitors at the middle of the line. The scheme recognizes the distortion of the voltage waveforms caused by the arcs usually associated with HIFs. The discrete wavelet transform (DWT) based analysis, yields three phase voltages in high frequency range which are fed to Clarke's transformation to produce ground and aerial modes voltage components for pattern recognition. The classifier is based on an algorithm that uses recursive method to sum the absolute values of high frequency signals generated over one cycle and shifts one sample. Characteristics of the proposed scheme are fully analyzed by extensive ATP/EMTP simulation studies that clearly reveal that the proposed method can accurately detect HIFs in EHV transmission lines and does not affected by different fault conditions such as fault distance and fault inception angle.