Abstract: Advanced measurement, control and two-way communication technologies lead more and more residents to participate in demand response（DR） through smart home energy management systems（SHEMSs）. However, uncertainties such as customer participation degree make it difficult to effectively quantify and evaluate the response capacity of residents. Firstly, a mixed-integer load model in the complex power consumption environment is established. And a day-ahead optimal scheduling model with autonomous decision-making incentive DR participation degree is created for smart homes, comprehensively considering time-ofuse price based and contract based DR strategies. Then, considering the uncertainty of customer behavior in response, a highdimensional parameter space is proposed based on the net load power and its multiple influencing factors such as participation degree and response time. The user response capacity could be quantified by the numerical expectation calculation of the envelope domain of net load surfaces before and after the response, based on which two gradient evaluation indices of response capability are proposed, considering both the incentive cost of power utilities and the response cost of customers. The given evaluation indices can provide guidance to power utilities for the design of incentive mechanisms and end users for the decision of response plans.Finally, the effectiveness of the proposed model and evaluation method are verified according to the simulation results.