Wind power frequency modulation energy prediction method and system, and computer equipment

[0057] The invention provides a wind power frequency modulation energy prediction method, such as figure 1 Shown: includes:

[0058] S1: Construct the historical wind speed time series data table and the historical wind speed spatial data table respectively based on the acquired historical wind speed data and the wind turbine geographical location information within the determined historical time period, and separate the historical wind speed time series data table and the historical wind speed spatial data table As the input of the LTC network link and the convolutional neural network link, the prediction information that does not consider the interaction of fans is output by the LTC network link, and the prediction information that considers the interaction of fans is output by the convolutional neural network link;

[0059] S2: add the prediction information of the under-consideration of the interaction of wind turbines and the prediction information of the consideration of th

[0073] The present invention based on the same inventive concept also provides a wind power frequency modulation energy prediction system based on LTC cyclic convolution network, including:

[0074] The prediction module is used to construct the historical wind speed time-series data table and the historical wind speed spatial data table respectively based on the historical wind speed data obtained within the determined historical time period, and use the historical wind speed time-series data table and the historical wind speed spatial data table as the LTC network chain respectively The input of the road and the convolutional neural network link, the prediction information that does not consider the mutual influence of the fan and considers the prediction information of the fan interaction is output by the LTC network link and the convolutional neural network link respectively;

[0075] The comprehensive prediction module is used to add the prediction information of the under-co