**4. Simulation Results**

In order to verify the accuracy and effectiveness of the proposed detection method, three models, back-propagation neural network (BPN), support vector machine (SVM), and RF were established. The parameters of models are as follows.


This paper selected the short-term load data of 50 urban electricity users from 15 March 2018 to 16 May 2018 in Hebei province, China. The dataset included six data types (peak, flat, and valley active power; power factor; voltage; and current) and three user types (industrial, commercial, and residential). Data were sampled at intervals of 30 min through smart meters. Among them, the unbalance ratio was 16.47%.
