Phase Identification in Distribution Networks with Micro-Synchrophasors

TL;DR

This paper introduces a new method for identifying phases in distribution networks using high-precision micro-synchrophasor data, leveraging voltage correlation patterns to accurately determine phase connections even in unbalanced and unlabeled systems.

Contribution

The paper presents a novel phase identification algorithm that utilizes cross-correlation of voltage magnitudes and phase angle differences from uPMU data, validated on both IEEE model and real feeder data.

Findings

Effective phase identification in unbalanced networks

Validated with IEEE 13-bus model data

Confirmed with real-world uPMU measurements

Abstract

This paper proposes a novel phase identification method for distribution networks where phases can be severely unbalanced and insufficiently labeled. The analysis approach draws on data from high-precision phasor measurement units (micro-synchrophasors or uPMUs) for distribution systems. A key fact is that time-series voltage phasors taken from a distribution network show specific patterns regarding connected phases at measurement points. The algorithm is based on analyzing crosscorrelations over voltage magnitudes along with phase angle differences on two candidate phases to be matched. If two measurement points are on the same phase, large positive voltage magnitude correlations and small voltage angle differences should be observed. The algorithm is initially validated using the IEEE 13-bus model, and subsequently with actual uPMU measurements on a 12-kV feeder.