2020 Jimenez, Victor Adrian and Will, Adrian and Rodriguez, Sebastian, Phase identification and substation detection using data analysis on limited electricity consumption measurements, Electric Power Systems Research, 187: 106450, 2020.
Resumen: One of the most common problems in the electricity sector is the lack of accurate information about the structure of the low-voltage distribution network, particularly the association between the customers and the substation’s phases. Identifying to which substation’s phase each customer is connected reduces the response time to contingencies, improves the detection of technical and non-technical losses, and enables the application of load balancing techniques, among other benefits. This paper presents a new method for phase identification and substation detection based on a correlation analysis of the variations of load consumption. Our method achieves accurate results with much fewer samples than the previous works, which is effective even if there are a low percentage of smart meters installed and missing data. We use statistical tests to avoid getting erroneous results from non-significant correlations values. It was tested on a public dataset and validated using real measurements from a neighborhood in Tucumán, Argentina. In the case of 200 customers and one to four weeks of data, we obtained an average accuracy of 80–95% if only 50% of the customers are measured, or 93–98% if all the customers are measured.