  The main subject of this paper is the sensing of network anomalies that span
from harmless impedance changes at some network termination to more or less
pronounced electrical faults, considering also cable degradation over time. In
this paper, we present how to harvest information about such anomalies in
distribution grids using high frequency signals spanning from few kHz to
several MHz. Given the wide bandwidth considered, we rely on power line modems
as network sensors. We firstly discuss the front-end architectures needed to
perform the measurement and then introduce two algorithms to detect, classify
and locate the different kinds of network anomalies listed above. Simulation
results are finally presented. They validate the concept of sensing in smart
grids using power line modems and show the efficiency of the proposed
algorithms.

Signal Processing