Abstract: The design and optimal operation strategy of the combined cooling, heating and power (CCHP) system for building clusters is the significant way to reduce energy cost of the building. The stochastic factors, such as energy demand and energy price, cannot be ignored in this optimization problem. Considering that the energy need of the building is stochastic variable, the stochastic mixed integer programming model is established, in order to solve the optimization problem of CCHP system for building clusters with minimization of the buildings’ total cost as objective. Furthermore, Benders multi-cut algorithm is proposed to solve the multi-objective programming model, which is aimed at finding the Pareto optimal decision of device configuration and running plan of CCHP system. Finally, the stochastic mixed integer programming model and Benders multi-cut algorithm are proved to be effective through experiment, and it is demonstrated that buildings have the less energy cost under collaborative strategy compared with non-cooperative strategy.

Key words: stochastic variable, benders multi-cut, pareto optimal decision, collaborative strategy

摘要： 面向建筑集群的冷热电联供系统的设计和优化是实现建筑楼宇能源成本节约的重要途径。随机因素对该联供系统的优化决策,具有显著的影响。考虑建筑楼宇的能源需求为随机变量,构建随机混合整数规划模型,解决以最小化建筑楼宇总费用为目标时建筑集群冷热电联供系统的优化问题;其次,提出采用Benders多割平面方法求解多目标规划问题,从而寻找冷热电联供系统的设备配置和系统运行的Pareto最优决策;最后,通过实验验证了模型和算法的有效性。实验结果表明建筑集群在协作模式下,相比于非协作模式,具有更低的总费用。

关键词: 随机变量, Benders多割平面, Pareto最优决策, 协作模式