For the purpose of popularization in application scenarios, this paper presents an economic dispatch method for the integrated energy systems considering the uncertainty of photovoltaic output and power load. Firstly, a mixed-integer nonlinear probability model for integrated energy systems is established. Secondly, the nonlinear model is segmented and linearized by the special sequence set (SOS-2) method. Then, the symmetric sampling strategy-based traceless transformation method is used to perform deterministic transformation, and to reveal the underlying probabilistic information. Finally, the calculation results of MILP and particle swarm optimization are compared and analyzed. The PuLp open-source modeling framework is utilized to model and solve the potential problems in a demonstration integrated energy project. The results show that, on one hand, the traceless transformation method which is based on the symmetric sampling strategy is efficient, and the generated probability density distribution can reveal the underlying probabilistic density distribution so that the operation information can be available for the system operator. On the other hand, compared with the particle swarm algorithm, the efficiency of solving MILP problems via the PuLp open-source framework can increase several times, which is suitable for real applications.