Traditional techniques are used for fault location detection in high-voltage transmission lines that
mostly depend on traveling waves and impedance-based techniques suffer from large errors
owing to the intricacy of fault modeling for various types of faults. Although single-line to ground
faults are dominant in high-voltage transmission lines, fault resistance as well as fault inception
angle might distort the current fault detection techniques. In addition, other types of faults exist
and that raises the need to develop an accurate fault detection technique to minimize the recovery
time. The current paper introduces a fuzzy and neuro-fuzzy algorithm to detect, analyze, and locate
different faults taking place in high-voltage transmission lines. A MATLAB Simulink Model is used
for analyzing different fault cases; fault detection and classification are done by the Fuzzy Interface
System (FIS), while fault location detection is done using the Adaptive Neuro-Fuzzy Interface
System (ANFIS). The introduced algorithm is evaluated via the Mean Square Error (MSE) technique.
The results showed full success in detecting and identifying different fault types, with a 0.0042
validity performance factor for fault location detection using ANFIS.