This paper presents a novel method which takes advantage of the K-means clusters and effective degree of clustering to recognize the abnormal data of electricity consumption by PLC communication. The novel clustering method was used to supervise the abnormal or missing data by the badly quality of PLC communication effectively. Firstly, we extract good historical data as the basic cluster according to the selected characteristic numbers. Then, the current moment of electricity consumption data take clusters analysis with the basic cluster to identify whether the data is abnormal or not. Finally, the paper conducted simulation to verify the method and the result of simulation showed that the method can verify the abnormal data effectively. Therefore, the method is beneficial for the supervision for data.