  Consumers with low demand, like households, are generally supplied
single-phase power by connecting their service mains to one of the phases of a
distribution transformer. The distribution companies face the problem of
keeping a record of consumer connectivity to a phase due to uninformed changes
that happen. The exact phase connectivity information is important for the
efficient operation and control of distribution system. We propose a new data
driven approach to the problem based on Principal Component Analysis (PCA) and
its Graph Theoretic interpretations, using energy measurements in equally timed
short intervals, generated from smart meters. We propose an algorithm for
inferring phase connectivity from noisy measurements. The algorithm is
demonstrated using simulated data for phase connectivities in distribution
networks.
