Wind power prediction model training method, wind power prediction method, device and medium

• Main Authors: PU ZHIYONG, LI XUTAO, ZHENG HAO, ZHU TIANLUN, XU JIANGNAN, WANG YUN
• Format: Patent
• Language: Chinese; English
• Published: 23.09.2022
• Subjects: CALCULATING; COMPUTING; COUNTING; ELECTRIC DIGITAL DATA PROCESSING; HANDLING RECORD CARRIERS; PHYSICS; PRESENTATION OF DATA; RECOGNITION OF DATA; RECORD CARRIERS

The invention provides a wind power prediction model training method and device, a wind power prediction method and device and a medium, and the training method comprises the steps: obtaining time sequence wind turbine data of a wind turbine and meteorological numerical data of a wind field where the wind turbine is located, the time sequence fan data represents fan data sorted according to time; performing feature extraction on the time sequence fan data based on a self-attention mechanism to obtain first feature data, and performing feature extraction on the meteorological numerical data based on a cross attention mechanism to obtain second feature data; fusing the first feature data and the second feature data to obtain training data; and training a pre-constructed deep neural network by using the training data to obtain a wind power prediction model. According to the technical scheme, the accuracy of wind power prediction is improved. 本发明提供了一种风功率预测模型训练方法、风功率预测方法、装置及介质，训练方法包括：获取风机的时序风机数据和所述风机所在风场的气象数值数据，所述