Aggregate Static Power Load Modeling in Coalmine
نویسنده
چکیده
-In order to overcome the defects of the traditional static load modeling in coalmine, a new modeling method is proposed in this paper. First, a new clustering method based on improved PSO algorithm is presented to classify the load data in order to reduce the number of load model before modeling. Second, RBF neural network based on improved PSO algorithm is put forward to establish aggregate load model. Finally, verified by an example, the method in this paper can greatly improve the accuracy of the model compared with traditional static load model. Key-Words:-aggregate static load model; particle swarm clustering algorithm; subtractive clustering algorithm; K-means clustering algorithm; radial basis neural network; power grid in coalmine
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