  Faults in electricity distribution networks have the potential to ignite
fires, cause electrocution, and damage the system itself. High current Low
Impedance Faults (LIF) are typically detected and mitigated via over-current,
distance, directional relays, fuses, etc. In contrast, while High Impedance
Faults (HIF) are equally hazardous, they are much more challenging to detect
due to the fault current being much lower than load currents and their
time-varying and nonlinear behaviour. Moreover, New Zealand distribution
networks are extensive and largely unmonitored beyond the substation, and
suitable HIF detection schemes are still an ongoing research challenge.
  To date, we have built a physical test facility for power system fault
analysis and developing and evaluating our sensing and fault detection system.
We have simulated LIF and HIF with different fault surface materials and
load-switching events. From the data collected, we have characterized the
unique fault behaviour for both LIF and HIF in 400V networks and trained a Deep
Learning classifier to recognize the type of fault present from its unique
signature. We have developed an outdoor pole mountable sensing system and have
installed this in Wellington Electricity's network for ongoing data collection
and evaluation.
  This paper will describe the test facility and our experience developing and
implementing the sensing system. The widest range of HIF phenomena observed was
in the fault experiments involving the tree branch. For brevity, therefore,
this paper reports on the results of just these tree-branch experiments. HIF
faults on other surface materials will be reported elsewhere. Finally, we will
detail the pole-mountable sensing system installed in Wellington Electricity's
network and the outcomes thus far.
