Abstract: The inherent strong instability and randomness of wind power supply pose a great challenge to the classic distribution network scheduling and operation system. In order to deal with the deficiency of the existing studies that ignore uncertain out-of-set risks and fail to fully consider demand flexibility, this paper establishes a demand flexibility-based distribution grid scheduling optimization model with wind power based on the objective quantification of the uncertain out-of-set expected risk of wind power. In order to solve the complex mixed integer nonlinear programming model, this paper proposes a two-layer optimization algorithm based on the coordination of the improved antlion algorithm with the branch-and-bound algorithm, and makes full use of the advantages of artificial intelligence algorithms and classic mathematical algorithms to solve the complex model rapidly. The case study results show that, compared with the existing advanced scheduling methods, the proposed method can make full use of demand flexibility, effectively reduce the risk of distribution network scheduling, and reasonably weigh the economy and risks of the scheduling plan. In the actual distribution network scheduling, this research can provide important guidance for realizing more efficient and stable distribution network scheduling with wind power.