Abstract: Driven by the dual-carbon goals, the large-scale grid connection of new energy sources has put forward higher requirements for the peak regulation flexibility and ramping flexibility of integrated energy systems. In this context, this paper proposes an optimization scheduling method for integrated energy systems that takes into account the uncertainty of flexibility supply and demand. Firstly, considering the forced outage of units and the prediction errors of new energy sources, an evaluation index for the system flexibility shortage rate is proposed. Then, based on the principal-agent game theory, with the power grid as the upper-level leader and the integrated energy system as the lower-level responder, the system flexibility shortage rate and the minimum operation cost of the integrated energy system are respectively taken as the upper and lower-level optimization objectives. Considering various constraints, a two-layer optimization scheduling model is established. The upper and lower layers are solved using the particle swarm optimization algorithm and Gurobi respectively. Finally, simulations verify the effectiveness of the proposed optimization scheduling method.