Detection of High Impedance Fault in Distribution Networks

This paper presents a new detection methodology for High Impedance Faults (HIFs) in power distribution networks based on Mathematical Morphology (MM). In the proposed method, the current signals are observed from the distribution feeder to detect HIFs. MM is used to extract the features in a time domain and a simple rule based algorithm to classify HIFs from other power system disturbances. An electric power distribution system was used to generate data such as HIFs, Low Impedance Faults (LIFs) and other switching transients using MATLAB/SIMULINK. From the results of the proposed method, it is found that the method could detect and differentiate HIFs from other disturbances in less time compared to other methods with high security and dependability. The function of the proposed method is not affected by various conditions such as the location, inception time, and type of fault.