Customer–Meter Box Relationship Identification Based on Load Switching Dynamic Response

Within the same low-voltage distribution network (LVDN), the short electrical distances between customers lead to highly similar steady-state voltage curves. This reduces the discriminative capability of traditional similarity metrics and limits the accuracy of customer–meter box relationship identification. To address this problem, this paper proposes a two-stage framework for identifying customer–meter box relationships based on dynamic responses to load switching. In the first stage, the consistency of the dynamic voltage responses of same-phase customers within the same meter box is used to calculate the similarity between customers voltage event sequences. The customers are then divided into single-phase clusters by phase. In the second stage, using the current events generated by load switching as the driving quantity and the cross-phase voltage events as the response quantity, a cross-phase cluster matching model is constructed. Combined with a voting mechanism and an optimized allocation strategy, this approach enables accurate matching of single-phase clusters across different phases and complete reconstruction of the meter box topology. A case study using high-frequency measurement data from an actual LVDN in Nanjing shows that the proposed method achieves an identification accuracy of 100%, demonstrating its effectiveness and superiority in identifying the meter boxes assignments of customers that are electrically close to one another.