There are errors in the topology record of the low-voltage distribution network, and its manual verification has high cost and low accuracy. An automatic topology identification method of a low-voltage distribution network based on T-type grey correlation degree and the K-Nearest Neighbor (KNN) algorithm is proposed. First, the T-type grey correlation degrees of the voltages between the users and the station area are calculated, and the KNN algorithm is used to judge the suspicious users of a station area by the set threshold value to identify the relationship between the user and the station area. Then, the T-type grey correlation degrees between user voltages are calculated under the new station area, and the suspicious users in the feeder are identified by the topological structure diagram. Finally, the users related to the suspicious users are found, and the location of the suspicious users in the feeder is located according to the characteristic that the voltage decreases gradually along the feeder. The results of case analysis show that the proposed method can automatically identify the user's station area and feeder line with high accuracy and good practicability. This work is supported by National Natural Science Foundation of China (No. 51677060) and Science and Technology Project of Hunan Electric Power Company (No. 5216A518000T).