  This paper presents a smart meter phase identification algorithm for two
cases: meter-phase-label-known and meter-phase-label-unknown. To improve the
identification accuracy, a data segmentation method is proposed to exclude data
segments that are collected when the voltage correlation between smart meters
on the same phase are weakened. Then, using the selected data segments, a
hierarchical clustering method is used to calculate the correlation distances
and cluster the smart meters. If the phase labels are unknown, a
Connected-Triple-based Similarity (CTS) method is adapted to further improve
the phase identification accuracy of the ensemble clustering method. The
methods are developed and tested on both synthetic and real feeder data sets.
Simulation results show that the proposed phase identification algorithm
outperforms the state-of-the-art methods in both accuracy and robustness.
