基于CNN-BiGRU网络的超短期风电功率预测OA

Due to the characteristics of multi-dimensional and large fluctuation of wind power data,it is difficult to predict wind power,this paper proposes a wind power prediction model based on convolutional neural networks(CNN)and bidirectional gated recurrent unit(BiGRU).The best combination of historical power and meteorological factors is selected by Pearson correlation coefficient in this model,the CNN network is used to extract the time series features of the original data,and then the BiGRU network is used to capture the time series dependence between these features,and finally,the wind power prediction values are obtained.The analysis of calculation examples shows that the CNN-BiGRU model proposed in this paper has higher prediction accuracy than the traditional BP and BiGRU neural network models.