Public buildings present substantial demand response (DR) potential, which can participate in the power system operation. However, most public buildings exhibit a high degree of uncertainties due to incomplete information, varying thermal parameters, and stochastic user behaviors, which hinders incorporating the public buildings into power system operation. To address the problem, this paper proposes an interval DR potential evaluation method and a risk dispatch model to integrate public buildings with uncertainties into power system operation. Firstly, the DR evaluation is developed based on the equivalent thermal parameter (ETP) model, actual outdoor temperature data, and air conditioning (AC) consumption data. To quantify the uncertainties of public buildings, the interval evaluation is given employing the linear regression method considering the confidence bound. Utilizing the evaluation results, the risk dispatch model is proposed to allocate public building reserve based on the chance constrained programming (CCP). Finally, the proposed risk dispatch model is reformulated to a mixed-integer second-order cone programming (MISOCP) for its solution. The proposed evaluation method and the risk dispatch model are validated based on the modified IEEE 39-bus system and actual building data obtained from a southern city in China.