The identification method of station-household relationship based on voltage characteristic analysis

The paper presents an innovative approach for identifying electrical station interconnections through voltage characteristic scrutiny. Initially, a comprehensive theoretical foundation is constructed, integrating understandings of residential transformers and the effects of their malfunctioning states. By delving into the dynamics of user voltage time series fluctuations, the distinctive patterns of voltage clusters within station zones are examined. To enhance algorithm precision, the Pearson correlation coefficient is deployed to assess user voltage curve similarities, complemented by a wavelet transform model for extracting voltage profile signatures. Utilizing GIS system datasets of neighboring stations, this approach executes anomaly detection and rectification in transformer relationships. Ultimately, pilot area empirical data serves as a test case to validate the proposed method’s efficacy, while concurrently forecasting limitations, suggesting future research avenues.