The bilateral uncertainty of wind power and demand response will have an important impact on the economic dispatch of power system. Firstly

fuzzy theory is used to fit the uncertain load under time-sharing tariff

and the uncertain set of wind power is built by using robust theory. At the same time

considering the bilateral uncertainty

a robust fuzzy mathematical model is established. Based on its equivalence

the transformation idea is determined to solve the model. Secondly

a robust fuzzy multi-objective scheduling model for the power system is established. Among them

multiple goals include the minimum carbon trading costs and the smallest comprehensive economic cost. The interior point method and multiple constraint processing strategy is used to improve the multi-objective bacterial population chemotaxis algorithm. The algorithm is used to solve the model and obtain the optimal solution of the objective function. Finally

the IEEE 10-node computer system and a wind farm are taken as examples to verify the feasibility and superiority of the proposed model.