Article: A data-driven full hierarchy topology identification method for low-voltage distribution area Journal: International Journal of Information and Communication Technology (IJICT) 2025 Vol.26 No.15 pp.78 - 95 Abstract: 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. Inderscience Publishers - linking academia, business and industry through research

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

Authors: Yutong Chen; Zhihong Zheng; Pengyu Zhang; Wei Wang; Chu Pei; Yinghua Li

Addresses: State Grid Shanxi Electric Power Company electric power Science, Research Institute, Shanxi, 030000, China ' State Grid Shanxi Electric Power Company electric power Science, Research Institute, Shanxi, 030000, China ' State Grid Shanxi Electric Power Company electric power Science, Research Institute, Shanxi, 030000, China ' State Grid Shanxi Electric Power Company electric power Science, Research Institute, Shanxi, 030000, China ' State Grid Shanxi Electric Power Company electric power Science, Research Institute, Shanxi, 030000, China ' State Grid Shanxi Electric Power Company electric power Science, Research Institute, Shanxi, 030000, China

Abstract: 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.

Keywords: low-voltage distribution station area; full hierarchy topology identification; the similarity of voltage curves; density peak K-means; DPK-means algorithm; Kendall correlation coefficient.

DOI: 10.1504/IJICT.2025.146370

International Journal of Information and Communication Technology, 2025 Vol.26 No.15, pp.78 - 95

Received: 11 Mar 2025
Accepted: 26 Mar 2025
Published online: 27 May 2025 *

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

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