User electricity stealing detection method based on data driving

The invention provides a user electricity stealing detection method based on data driving, and the method comprises the following steps: 1, obtaining the electricity utilization data of n users in a certain transformer area through an electricity utilization information collection system, obtaining the load data of a 96-point power curve every day, and carrying out the data preprocessing; 2, converting the preprocessed discrete point data into a second-order matrix by adopting a GASF (Grubrum Angle Field), and extracting data features; 3, performing dimension reduction on the GASF matrix by adopting a principal component analysis method to obtain a data feature matrix; step 4, classifying the data feature matrix after dimension reduction by using a K-means clustering method to obtain a clustering center sequence; and 5, calculating the similarity of the clustering center sequence by adopting a Pearson correlation coefficient, and setting a threshold value to judge an abnormal user. According to the technical