A Study of Methods for Identifying Single-Phase Consumers Connected to Individual Distribution Network Phases Based on Voltage Profiles
DOI:
https://doi.org/10.24160/0013-5380-2026-8-78-89Keywords:
low-voltage network, phase identification, single-phase consumers, intelligent metering devices, voltage profiles, clusterizationAbstract
The article compares the effectiveness of using three most well-known clustering methods (hierarchical, K-means and DBSCAN) for phase identification of single-phase consumers connected to a 0.4 kV distribution network. The above-mentioned problem was solved proceeding from voltage profile data by applying the clustering algorithms compared for three proximity markers: 1) the proximity of the voltage profiles correlation to unity; 2) the sum of the modules of relative voltage difference; 3) the combination of markers 1 and 2. The studies were carried out with reference to the actual half-hour voltage profiles received during 402.5 hours from modified CE-208 electricity meters of 33 single-phase household consumers. It has been found that the most effective algorithm is that based on DBSCAN clustering in combination with a combined proximity marker, which provides 100% accuracy of identifying the loads connected to individual phases when using measurements of half-hour profiles at a 3.5 h interval. The study results will be of interest to developers of automated information and measurement fiscal electricity metering systems and automated dispatch control systems for distribution networks in designing subsystems for monitoring and control of 0.4 kV network operation modes.
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