This paper presents a new strategy based on multivariate
statistical analysis for fault location and classification in
power distribution networks with distributed energy resources,
variable loads, and switches enabling grid reconfiguration. The
statistical method relies on impedance measurements acquired
at the substation buses to build a data-driven model of the
network operating conditions with dimensionality reduction,
and considers a few reference scenarios representing standard
operating conditions and short-circuit operation to perform fault
location and classification with use of similarity criteria in the
principal component subspace. Moreover, this paper includes
a case study with a real-based low voltage power distribution
network to test and validate the methodology
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