Aggregate static load modeling in power grid with environmental characteristics

In practice, there are many defects that underground load model is built by using the traditional static load model in coal mine. To enhance the accuracy of load model, a new clustering method based on improved PSO algorithm is presented in this paper. This new clustering method is used to classify the load data in order to reduce the number of load model before modeling. Then, RBF neural network based on improved PSO algorithm is proposed to establish aggregate load model. Verified by an example, compared with traditional static load model, the method in this paper can greatly improve the accuracy of the model.