English

Phase Identification of Smart Meters Using a Fourier Series Compression and a Statistical Clustering Algorithm

Applications 2023-02-10 v1 Systems and Control Systems and Control

Abstract

Accurate labeling of phase connectivity in electrical distribution systems is important for maintenance and operations but is often erroneous or missing. In this paper, we present a process to identify which smart meters must be in the same phase using a hierarchical clustering method on voltage time series data. Instead of working with the time series data directly, we apply the Fourier transform to represent the data in their frequency domain, remove 98%98\% of the Fourier coefficients, and use the remaining coefficients to cluster the meters are in the same phase. Result of this process is validated by confirming that cluster (phase) membership of meters does not change over two monthly periods. In addition, we also confirm that meters that belong to the same feeder within the distribution network are correctly classified into the same cluster, that is, assigned to the same phase.

Keywords

Cite

@article{arxiv.2212.12650,
  title  = {Phase Identification of Smart Meters Using a Fourier Series Compression and a Statistical Clustering Algorithm},
  author = {Jeremy J. Chiu and Albert Wong and James Park and Joe Mahony and Michael Ferri and Tim Berson},
  journal= {arXiv preprint arXiv:2212.12650},
  year   = {2023}
}

Comments

5 pages, 6 figures, 4 tables

R2 v1 2026-06-28T07:51:30.776Z