Power flow data real-time processing and wind power forecasting based on Flink and GRU

The innovative combination of computer technology and power system, It provides a new idea for the real-time processing of power flow data and the precision of wind power prediction. Aiming at the dynamic characteristics of the power flow data in the wind farm and the high precision requirement for the wind power prediction, A wind power prediction model combining Apache Frink framework and gated cycle unit is proposed. The model realizes accurate prediction of wind power through real-time data processing and efficient capture of long-term and short-term time series. In the index test, the precision of the model in the training set is 99.23%, the F1 score is 99.25%, and the recall is 99.27%.In the prediction experiment, the R2 of the model is 0.97, which is much higher than that of the comparison model. The experimental results show that the proposed model uses its unique data cleaning mechanism and multi-module mechanism. The reliability of the wind power prediction is effectively improved, It provides a new path for the application of smart grid technology in power flow data processing and wind power forecasting.