Doaa Khalil Ibrahim

n/a

High impedance faults (HIFs) are difficult to be detected by overcurrent protection relays. This paper presents an ATP/EMTP fault simulations studies based algorithm for high impedance fault detection in extra high voltage transmission line. The scheme recognizes the distortion of the voltage waveforms caused by the arcs usually associated with HIF. The discrete wavelet transform (DWT) based analysis, yields three phase voltage in the high frequency range which are fed to a classifier for pattern recognition. The classifier is based on an algorithm that uses recursive method to sum the absolute values of the high frequency signal generated over one cycle and shifting one sample. A HIF model of distribution is modified for EHV transmission lines. Characteristics of the proposed fault detection scheme are analyzed by extensive simulation studies that clearly reveal that the proposed method can accurately detect HIFs in
the EHV transmission lines.

Faults on distribution circuits are normally detected by simple overcurrent relays. Faults through high impedance (HIF) such as dry earth don’t have sufficient current to operate overcurrent relays. In some cases, fault current is less than the normal current. The broken cables laid on the soil, can be left energized for long periods of time. This presents a serious hazard to the general public with risks of electric shock, fire, etc. This paper describes a new scheme for high impedance fault detection using the concept of digital communications. The proposed model posses a high capability of distinguishing the HIF from normal switching conditions.

Coupling Capacitor Voltage Transformer (CCVT) secondary voltages, normally applied to conventional schemes, do not comprise appropriate information for schemes that operate on high frequency fault generated transients. However it is possible to capture the required travelling wave information contained in fault transients using a high frequency tap from a CCVT. This paper presents an ATP/EMTP fault simulations studies based algorithm for half cycle high impedance fault detection. The proposed scheme implemented on two different models of HIF in extra high voltage mutually coupled double-ended transmission lines. The scheme recognizes the distortion of the voltage waveforms caused by the arcs usually associated with HIFs. The high pass filter tap yields three phase voltage in the high frequency range which are fed to Clarke’s transformation to decouple the traveling waves of the mutually coupled lines and produces ground mode and aerial modes voltage components to
the classifier for pattern recognition. The classifier is based on an algorithm that uses recursive method to sum the absolute values of the high frequency signal generated over one cycle and shifting one sample. Characteristics of the proposed fault detection scheme are analyzed by extensive simulation studies that clearly reveal that the proposed method can accurately detect HIFs in the EHV transmission lines within only half a cycle from the instant of fault occurrence. The reliability of the proposed scheme does not affected by different fault conditions such as fault distance and fault inception angle.

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.