In order to solve the problems of low accuracy and incomprehensive recognition of the topological relationship between households in the station area and the incomplete recognition results in traditional methods, a method for identifying topological relationships between household changes
in low-voltage stations based on correlation analysis algorithm and probabilistic decision method is proposed. The BIRCH method is used to cluster the topological relationship characteristics of the household line changes in the low-voltage station area, and the topological relationship characteristics
are obtained through clustering parameter initialization, clustering implementation and clustering evaluation, and the user phases in the topological relationship are identified according to the feature clustering results. The correlation analysis method is used to analyze the similarity of
the voltage sequence of the points to be identified and the comprehensive similarity of all the faults of the target distribution transformer and the auxiliary distribution transformer, and set a similarity threshold to determine whether the points to be identified belong to the same station
area. Finally, based on the probabilistic decision-making method, the identification of the topological relationship of the low-voltage station area household line change is completed. The experimental results show that this method can not only identify the topological relationship of single
distribution transformer outage, but also identify the topological relationship of multiple distribution transformer outage. The accuracy of the identification result is high, and the identification loss function is low, which indicates that the identification result of this method is reliable
and comprehensive.
