Research on Accurate Wind Power Prediction by Integrating Deep Learning and Intelligent Optimization Algorithm
Aiming at the limitations of existing wind power prediction models in handling these complex data,a series of prediction models based on improved deep learning networks and intelligent optimization algorithms are proposed.By integrating a long short-term memory(LSTM)neural network,gated recurrent unit(GRU)and time-varying deep feed-forward neural network(ForecastNet),and combining residual network and sparrow search algorithm(SSA)for model optimization.Experimental results show that the prediction performance of the proposed integrated model on multiple real wind farm datasets is better than existing prediction methods,demonstrating excellent prediction accuracy and real-time performance.
NETL
NSTL
万方数据
