Probability Prediction of Ultra-short-term Wind Power Based on Temporal Pattern Attention

Improving the prediction accuracy is a key problem for wind power probability prediction research. The multi-source numerical weather prediction were integrated to reduce the prediction error, the temporal pattern attention was used to select the input information adaptively, the temporal convolutional network was used to extract the multi-time scale probability features, and the mixed Beta distribution was used to construct the prediction probability information. The simulation results show that the convergence of model training can be improved effectively by integrating multi-source numerical weather prediction with temporal pattern attention, and the prediction results have higher accuracy.