Short-term wind power forecast based on Long Short Term Memory

As the impact of climate change on the environment increases, the demand for new energy sources is growing. In the development of renewable energy, wind power generation is an important technology that can use wind energy to generate electricity. However, due to its unstable nature, the forecasting of wind power generation has become one of the most important problems in wind farm management. In this paper, historical wind power data is selected as input to establish a wind power prediction model based on Long Short Term Memory (LSTM). By training LSTM model, the prediction of wind power in next 12 hours is realized. Result shows that the model has certain feasibility and accuracy, can accurately predict the future short-term wind power generation, and has a wide range of application value.