The invention discloses a
power grid abnormal
electricity utilization detection method based on an attention mechanism and a residual network, and the method comprises the following steps: S1, data collection: carrying out the high-frequency collection of massive
electricity utilization information of a user through a large number of intelligent ammeters, and collecting a large number of power data; s2, preprocessing data; S3, selecting a training
data set and a
test data set; s4, setting initial parameters of the model; s5, training a classification
algorithm based on the attention mechanism and the residual network, and performing model training on the classification
algorithm based on the attention mechanism and the residual network by using the training sample; s6, predicting
power consumption data; and S7, analyzing a result. According to the method, abnormal power utilization detection of the
power grid is achieved with high precision, in practical application, the
algorithm capacity is quite stable, and the method has good
processing capacity for complex environments and data.