The electric power markets have enforced new power service quality that makes fault location in power distribution systems an obligatory issue. This paper presents a novel high impedance fault detection and location approach based on wavelet transform and artificial neural networks (ANNs). The system simulation of 20kV underground power distribution has been implemented using EMTP/ATP software. The simulated data is analyzed using advanced signal processing technique based on wavelet analysis to extract useful feature from signals and this is then applied to the artificial neural networks for locating high impedance faults in a practical underground distribution system. The paper concludes by comprehensively evaluation the performance of the technique developed in the case of high impedance faults. The results indicate that the fault location technique has an acceptable accuracy under a whole variety of different fault conditions and system parameter changing with cable ageing and altering of load taps position.
