The users’ electricity consumption will affect the voltage deviation from the normal value and affect the reliability of power supply of distribution system. In order to realize the optimal management of power supply

an identification method for relationship between transformer and users based on fuzzy c-means clustering is proposed. Firstly

the bad data from smart meter is identified and repaired

and then the principal component analysis (PCA) method is used to extract the features of the data

and the different objects are simulated for fuzzy c-means classification. According to a variety of data characteristics

users are classified into three levels: large

medium and small. The Pearson correlation coefficient is used to clarify the influence of electricity consumption behavior of different types of users on the voltage in the substation area

and to build a clear relationship between transformer and users. Taking a residential area in Guangzhou for example

the effectiveness and applicability of the proposed identification method are verified by comparing the historical data with multi-scene simulation. The results show that the proposed identification method can quickly identify the electricity consumption behavior of some special users and the abnormal impact on the voltage of the substation area.