Wind power prediction based on NGO-LSTM

At present, wind energy is mainly utilized through wind power grid connections. However, because of the uncertainty of wind energy, the grid connection will inevitably have an impact on the system. In order to adjust the grid dispatching plan in real time and improve the grid’s capacity to absorb wind power, a short-term wind speed prediction method based on NGO-LSTM was proposed. Taking the measured data of wind farms as an example, the prediction accuracy of the proposed method is compared with that of existing algorithms. Experimental results show that the R 2 of the NGO-LSTM coupling model is closest to 1, and the RMSE, MAE, and MAPE are all smaller than the other two models, verifying the effectiveness and advanced nature of the proposed method.