China's dual carbon target requires an increasing share of new energy in the power grid. To enhance the new energy consumption rate， a source-load-storage collaborative scheduling strategy based on Stackelberg game is proposed for the power system consisting of virtual power plants （VPPs）， load aggregators （LAs）， and energy storage systems （ESSs）. The autonomous VPP serves as a leader at the upper level， while the LA with demand response capability， both a power purchaser and a consumer， acts as the follower at the lower level. A win-win situation can be achieved by new energy consumers and the source-load-storage system through a game of pricing and energy usage strategies between the upper and lower levels. The results of the case study on the proposed strategy show that it is possible to create the win-win situation between source， load and storage by taking time-of-use pricing and game theory， and to increase the new energy accommodation capacity. And ESSs can alleviate fluctuations of loads and new energy outputs， rise the return of VPPs at source end， lower the electricity costs of LAs with the premise of ensuring energy uses' satisfaction， ensure energy consumption at the load end， enhance the demand responsiveness of customers， and expand the room for new energy's grid connection. Taking distributed Genetic Algorithm and Quadratic Programming （GA-QP） in solving process is of good convergence speed and effectiveness，and able to protect the privacy of all parties in the game.
