A novel ultra short-term wind power prediction model based on double model coordination switching mechanism

Abstract

Ultra-short-term wind power provides technical support for unit control and scheduling to optimize the power system. Wind fluctuation is the main factor that makes it difficult to accurately predict wind power output. To improve the power prediction accuracy of the wind power fluctuation period, a combined prediction model that can automatically switch between two models is proposed. For small fluctuations in wind speed, we construct a sequence-to-sequence model that integrates temporal and spatial attention mechanisms for power prediction. The prediction model switches to the wind power curve model when the wind speed fluctuates significantly, which reflects the static characteristics of the unit. We determine the appropriate wind speed fluctuation threshold on the verification set, so that the two prediction models can coordinate the switchSimulation experiments were carried out on the data set provided by a wind farm in Inner Mongolia, China. The normalized RMSE of the forecast in the future 4h is 0.1405.