Abstract: A Regional Integrated Energy System（RIES） is one of the effective ways to solve the problems of low efficiency of social energy utilization and difficult consumption of renewable clean energy. First, the RIES model including wind power, various energy storage and Power-to-Gas（P2 G） equipment is established. In view of the flexible characteristics and dispatchable value of electric, gas and thermal loads, and the coupling relationship between the three loads in RIES, an integrated demand response model that takes into account electric, gas and thermal loads is proposed, and the uncertainty of wind power contribution is considered in a typical scenario set to establish the regional integrated energy system optimization dispatch model. The model is optimized for the lowest combined operating cost, lowest carbon footprint and highest energy efficiency utilization, and solved by using the Non-Dominated Sorting Genetic Algorithm（NSGA-II） to output the Pareto optimal frontier solution set. Four scenarios are set up in the simulation case to analyze the impact of electricity, gas and heat demand response and access of P2 G and energy storage equipment on the operational optimization of an RIES. The results show that the multi-objective optimization scheduling model can not only improve energy efficiency, but also ensure environmental protection and the economic operation of the system.