综合能源网络基于多能源技术的灵活性，可以为地区及更上级的能源系统提供服务。由于非线性因素和建模的复杂性，其运行不确定性在优化控制建模时常常被忽略。为此，提出了一个包含多能源可控装置的综合能源网络优化控制框架。并将改进型混合整数线性规划(mixed integer linear programming，MILP)和非线性网络方程的线性逼近用于该框架的二阶段迭代建模。在MILP优化阶段，基于电功率、热功率和天然气功率均衡等效模型，并引入不确定概率因子，将不确定运行进行集合约束，建立成本最小化的优化目标函数。在第二阶迭代计算阶段，使用非线性综合网络模型，引入微分参数的随机概率因子集合，为提高迭代逼近计算运行效率及可行性，将线性约束独立参数进行动态修正策略引入迭代过程中。最后，所提出的优化控制模型被应用到一个工业园区，实验结果表明，该优化模型算法可以最大化地节约运行能耗成本，确保计算效率的同时能够适应综合能源网络不确定性工况。

Based on the flexibility of multi energy technology, integrated energy network can provide services for regional and higher level energy systems. Due to the nonlinear factors and the complexity of modeling, the operational uncertainty is often ignored in optimal control modeling. Therefore, this paper proposes an integrated energy network optimization control framework including multi energy controllable devices. The improved mixed integer linear programming (MILP) and the linear approximation of nonlinear network equations are applied to the two-stage iterative modeling of the framework. In the MILP optimization stage, based on the power balance equivalent model of electricity, heat and natural gas, and introducing the uncertain probability factor, the uncertain operation is set constrained, and the optimization objective function of cost minimization is established. In the second iteration stage, the nonlinear synthesis network model is used, and the random probability factor set of differential parameters is introduced. In order to improve the efficiency and feasibility of iterative approximation calculation, the dynamic correction strategy of linear constraint independent parameters is introduced into the iteration process. Finally, the proposed optimization control model is applied to an industrial park, and the experimental results show that the optimization model calculation method can maximize the energy consumption cost, ensure the calculation efficiency and adapt to the uncertainty of the integrated energy network.