Wind power plant wake flow and power prediction method based on generative adversarial network model

The invention discloses a wind power plant wake flow and power prediction method based on a generative adversarial network model. The wind power plant wake flow and power prediction method comprises the following steps: 1) constructing a single-fan wake flow prediction model based on a transformer model and a conditional generative adversarial network; 2) constructing a multi-fan wake flow superposition prediction model based on a convolutional neural network, and training and verifying the two models by analyzing the wake flow model and generating a training data set through numerical simulation; and 3) predicting the wake flow field and power of the wake flow of the wind power plant according to the single-fan wake flow prediction model and the multi-fan wake flow superposition prediction model. The deep learning model technology is adopted, the wake flow prediction precision close to numerical simulation can be achieved while efficient calculation is guaranteed, and the method can be rapidly deployed in va