Abstract: With the implementation of the "double-carbon" strategy, the penetration ratio of wind & solar energy and other new energy sources continues to increase. The participation of the demand-side resource in the active power dispatching is one of the important ways to balance the source and load and improve the absorption rate of new energy. However, the multiple uncertainties on the source and load side have put forward new requirements for the management of multiple types of energy in the integrated energy system. In this context, this paper proposes a collaborative optimization of scheduling and consuming, and constructs a two-tier optimization model of energy management and pricing. Firstly, the stochastic robust optimization proposed in this paper is adopted in the upper level energy management model to solve the problems of new energy generation time series volatility, load and response uncertainties faced by the integrated energy system scheduling. Secondly, in the lower energy pricing model, the maximum local absorption rate of new energy in the system is taken as the target. Through the price change signal to guide the users' reasonable consumption, the load curve is optimized, and the wind and optical power caused by the safe and stable operation in the upper control is absorbed; Then, by applying the strong duality theorem of linear optimization and the column sum constraint generation algorithm, the upper layer model is transformed into a mixed integer linear programming problem. The commercial solver YALMIP/GUROBI is used to solve the two-layer optimization model. Finally, an example analysis verifies the optimization method in this paper is able to take into account both the robustness and economy of the system operation. It also effectively promotes the consumption of new energy under the scenario of a high proportion of new energy access.