Fault Location in Low Voltage Smart Grids Based on Similarity Criteria in the Principal Component Subspace

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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