The invention belongs to the field of electric power topology big data analysis, and particularly relates to a method for identifying a transformer area user-transformer relation based on electric quantity correlation of user branches. The invention includes the following steps: S1, obtaining transformer area user branch data, power consumption data and adjacent transformer area data; S2, establishing an electric quantity correlation analysis model of the user branches; S3, using the electric quantity correlation analysis model to diagnose the affiliation relationship between the user branches and the transformer area; and S4, outputting a transformer area user-transformer relation result. On the basis of user classification, user branch data and adjacent transformer area data, positive correlation characteristics are provided by utilizing a Pearson's correlation coefficient, and the affiliation relationship between the user branch and the plurality of transformer areas is diagnosed by utilizing the quantitative trend change of positive and negative correlation coefficient values of the user branch and the two or more transformer areas, so that the transformer user relationship identification is realized. Point selection strategies participating in correlation calculation are optimized for users with different electricity utilization characteristics, positive and negative correlation characteristics are enhanced, the recognizable user range is further expanded, and the accuracy of table user relation recognition is improved.