Abstract: The accurate predition of wind power is crucial for enhancing the efficiency of wind energy utilization and achieving sustainable development of the power system. In view of this, a multi-step wind power prediction model based on the improved variational modal decomposition (VMD) with Informer is proposed in this paper. Firstly, the original meteorological factors such as wind speed, wind direction, and pressure are filtered using the random forest model. Secondly, the wind power signal is decomposed by the pelican optimization algorithm-improved VMD algorithm to enhance the accuracy of wind power sequence prediction. Thirdly, multi-step wind power prediction is performed using the Informer model. Finally, the superiority of this model in multi-step wind power prediction is verified through multi-dimensional comparison with other models. The case results demonstrate that the wind power multi-step prediction model based on the improved VMD with Informer exhibits excellent prediction performance and can provide reference for wind power prediction.