Abstract: The industrial users in the smart park use more energy, have a high level of automation, and are closely coupled with multiple energy sources. They play an important role in participating in carbon emission reduction and demand response. Consequently, different power sources of industrial users are taken into consideration, the peak-shaving instruction from senior authorities is set as the inner optimization target, and the lowest daily operating cost of the system is set as the outer optimization target, so that a mixed-integer nonlinear optimization model is established that considers user participation in comprehensive demand response under a stepped carbon trading mechanism model. Furthermore, the model is converted into a mixed-integer linear programming problem which is solved. Finally, the user's operating strategy in two modes of traditional economic dispatch and participation in comprehensive demand response can be obtained. The analysis of calculation examples shows that the proposed strategy can further improve the low carbon and economical efficiency of users in the park, and provide different response strategies for users to participate in demand response in different modes. Under the step-by-step carbon trading mechanism, user's demand response method is changed to thermal demand response priority, enabling users to reduce carbon emissions and total operating costs while achieving the peak reduction target.