Short-Term Wind Speed and Wind Power Prediction Based on Meteorological Model Modification

Abstract

Accurate prediction of wind speed and wind power is of great significance to the operation, planning, dispatching and control of power system. In order to make full use of the effective information provided by SCADA system and NWP to further improve the prediction accuracy of wind speed and wind power. A short-term wind speed and wind power prediction method based on meteorological correction model is proposed in this paper. Firstly, the meteorological model based on matrix completion algorithm is established to modify the meteorological data. Secondly, the network is trained with the data of meteorological model modification as input and the actual power of fan as output, and the prediction model based on LSTM network is established. Finally, the short-term prediction of wind speed and wind power is completed. The measured data from a wind farm is used for verification. The research results show that the information in multiple data sources can be well used in the proposed method to complete the prediction of wind speed and wind power. And in the future, the waste of wind resources can be effectively reduced, so as to realize the economic and stable operation of the power grid.