Abstract: The load fluctuation and the dynamic pipeline storage of natural gas have brought great challenges to the integrated electric-gas distribution system. In order to solve the problems, this paper proposes a dynamic distributionally robust optimization model based on the combination of chance constraint and the Wasserstein distance. Considering three different demand response loads, i.e. the reducible, transferable and replaceable loads, and the pipeline storage characteristics during gas transmission, a dynamic optimization model of the integrated electric-gas distribution system with demand response is established. As for the uncertainty problems of the electrical and gas loads in demand response, the paper proposes a distributionally robust ambiguity set based on the Wasserstein metric of uncertain variables. Combined with the chance constraints, this model restricts the inequality to a certain probability confidence interval to further improve the stability of the model. The dual theory and the conditional value at risk approximation method are used to transform the proposed model into a linear programming problem. Based on the modified 33 node electric distribution network and the Belgium 20 node gas distribution network, the simulation results illustrate the proposed model can effectively reduce the comprehensive costs and improve the consumption capacity of the wind power.