A decentralized fault detection technique for detecting single phase to ground faults in power distribution systems with resonant grounding

IEEE This paper presents a decentralized fault detection technique for power distribution systems with resonant grounding (RG). The aim of this paper is to detect single phase to ground (SPG) faults and identify the faulty feeder within three cycles of the fault occurrence. In the proposed technique, faults are firstly detected based on the neutral voltage displacement. The pre-fault and postfault voltages (phase to ground) are then used to identify the faulty phase. Finally, the faulty feeder (as well as the faulty area of a long feeder) is identified from the relationship between the initial transient of the zero-sequence current and the faulty phase voltage just after the occurrence of faults. A signal processing tool called mathematical morphology (MM) is utilized to identify the faulty feeder. To identify the faulty feeder, it is also required to know the fault occurrence time which is estimated using the slope of the neutral voltage. The main feature of the proposed scheme is that this technique only uses voltage and current signals from the corresponding voltage transformers (VTs) and current transformers (CTs). Therefore, it does not require communication among protection devices in the same or different feeders to identify the faulty feeder. The proposed technique also has the ability to distinguish the nature of faults, i.e., whether the faults are permanent or temporary. The effectiveness of the proposed scheme is tested, on an IEEE test system as well as on a practical test system, using < formula > < tex > ${MATLAB/SimPowerSystems}$ < /tex > < /formula > . Simulation results show that the proposed technique can quickly detect the SPG faults in a RG power distribution system and identify the faulty feeder. It is also capable of distinguishing faults from other disturbances. Moreover, it works under different compensation levels (CLs) as well as for different fault inception angle (FIAs).