Research on Wind Speed Prediction of Wind Power System Based on GRU Deep Learning

摘要

High precision and reliable wind speed forecasting is important for the management of the wind power. Under this background, the prediction system is established by using the GRU (Gated Recurrent Unit), which is based on deep learning prediction model and combining the relevant historical data of wind power system. The power regulation capability of wind energy and solar energy equipment are improved. Then, the impact of randomness and intermittentity of wind energy on the output power quality of wind turbine is effectively reduced. Simulation results show that the prediction algorithm has high prediction accuracy, and the prediction system provides support for network structure analysis and control strategy of multi-energy system.