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Faults in electricity distribution networks have the potential to ignitefires, cause electrocution, and damage the system itself. High current LowImpedance Faults (LIF) are typically detected and mitigated via over-current,distance, directional relays, fuses, etc. In contrast, while High ImpedanceFaults (HIF) are equally hazardous, they are much more challenging to detectdue to the fault current being much lower than load currents and theirtime-varying and nonlinear behaviour. Moreover, New Zealand distributionnetworks are extensive and largely unmonitored beyond the substation, andsuitable HIF detection schemes are still an ongoing research challenge.  To date, we have built a physical test facility for power system faultanalysis and developing and evaluating our sensing and fault detection system.We have simulated LIF and HIF with different fault surface materials andload-switching events. From the data collected, we have characterized theunique fault behaviour for both LIF and HIF in 400V networks and trained a DeepLearning classifier to recognize the type of fault present from its uniquesignature. We have developed an outdoor pole mountable sensing system and haveinstalled this in Wellington Electricity's network for ongoing data collectionand evaluation.  This paper will describe the test facility and our experience developing andimplementing the sensing system. The widest range of HIF phenomena observed wasin the fault experiments involving the tree branch. For brevity, therefore,this paper reports on the results of just these tree-branch experiments. HIFfaults on other surface materials will be reported elsewhere. Finally, we willdetail the pole-mountable sensing system installed in Wellington Electricity'snetwork and the outcomes thus far.

Monitoring and Detection of Low-current High-Impedance Faults in Distribution Networks