The invention relates to a short-term wind power combination prediction method which comprises steps of 1, extracting wind power sequential data from supervisory control and data acquisition (SCADA) related to a wind power plant; 2, performing sequence analysis on the extracted wind power sequential data through ensemble empirical mode decomposition; 3, reconstructing phase space of sequences obtained through the ensemble empirical mode decomposition; 4, according to the data obtained by reconstructing the phase space of the sequences, training the established wavelet neural network prediction model, and superposing predication results of the sequences to obtain a wind power prediction result; 5, performing error analysis on the wind power prediction result. By means of the short-term wind power combination prediction method, the modeling process is simple and practical, and wind power predication can be quickly and effectively performed. Therefore, the short-term wind power combination prediction method has great significance in safety, stability, management and running of a power system, and has wide popularization and application value.