Abstract: It is crucial to realize both economical operation and good tracking performance of the virtual power plant（VPP）with uncertain source and load. This paper proposes an optimal scheduling method of VPP based on variational mode decomposition and dualmode economic model predictive control. Firstly,the original power curves of wind power,photovoltaic power and load are decomposed by the variational mode decomposition algorithm optimized by the whale algorithm,and new high and low frequency components are reconstructed by mutual information entropy. Then,considering the frequency characteristics and different operating characteristics of controllable equipment,the optimal scheduling model of VPP is designed. An optimization operation control strategy of VPP in terms of dual-mode economic model predictive control is presented on this basis. Operating economy is improved through economic model predictive control through Mode1,and better tracking performance is maintained with the help of auxiliary controller through Mode 2.Finally,the case analysis demonstrates that the signal reconstruction result through the variational mode decomposition after parameter optimization is enhanced. The proposed dual-mode economic model predictive control strategy can coordinate the output of different type of equipment and improve the operation economy of VPP on the basis of ensuring it to track the optimal point of steady state.