With the gradual increase of the proportion of wind power in the power system, the accurate prediction of wind power is of great significance to the safe and stable operation of the power system. However, the random and intermittent nature of wind power greatly affects the accurate prediction of its power. Therefore, this paper proposes a quadratic decomposition combination LSTM short-term wind power prediction model.Firstly, the EMD technique is used to decompose the original wind power series into several intrinsic mode components.Then, SE technique is used to recombine the components into three sequences: high, middle and low frequency. SSA-VMD technique is used for high frequency mode aliasing.Finally, SSA algorithm is used to optimize the parameters of LSTM and wind power prediction is completed.A wind farm in Hubei Province is used to verify the proposed model and compare with other models.The results show that the MAE, RMSE and MAPE of the proposed model are 5.79 KW, 5.64 KW and 17.38%, respectively.