Introduction - If you have any usage issues, please Google them yourself
Aiming at short-term wind power prediction, a kernel-based learning machine combination prediction method based on empirical wavelet transform preprocessing is proposed. Firstly, the EWT is used to adaptively decompose the measured wind speed data of the wind farm and extract the modal signal components with Fourier tight support. The KELM prediction model is constructed for each component. Finally, the output of each prediction model is superimposed to obtain the wind speed prediction value. The wind power characteristic curve of the wind farm can be obtained corresponding to the predicted wind power.