A data-driven full hierarchy topology identification method for low-voltage distribution area

The inaccurate topology of low-voltage distribution station area leads to inefficient fault disposal and affects user experience. In view of the above situation, this paper proposes a data-driven full hierarchical topology identification method for low-voltage distribution station areas. The density peak K-means (DPK-means) algorithm is employed in this method to discern the user's phase based on the similarity analysis of 'distribution transformer-branch box-metre box-user'. Furthermore, the Kendall correlation coefficients between the voltage curves at each hierarchy in the low-voltage distribution station area are calculated and normalised to identify subordinate relations. The proposed method enables the recognition of user phases and hierarchical subordinate relations within the low-voltage distribution station area. Finally, the effectiveness of the proposed method is analysed and verified in the actual distribution station area.