工业蒸汽系统是石油化工等能量密集型产业重要的能量消耗和污染物排放系统。以系统模型为基础，以综合优化为核心的系统优化决策是过程工业实现节能减排的重要手段。随着我国能源结构、物质结构和产业结构的调整，多不确定性信息和多目标需求下，基于确定工况模型的系统综合优化方法难于获得强鲁棒性的最优决策方案。为了克服这一困难，本项目力求通过工业过程信息的深度融合，建立不确定条件下蒸汽系统的用能模型，根据不同目标鲁棒贡献度进行系统综合优化方法研究，具体研究内容涵盖四个方面（1）预测和定量描述不确定因素对系统运行特性的影响；（2）辨识对系统各优化目标产生影响的关键结构和变量；（3）建立系统综合优化数学模型；（4）研究基于模型的大规模多目标综合优化问题求解方法。项目的成功开展能够给出不确定条件下蒸汽系统运行特性模型及最优运行方案集，有效提高系统能量利用效率、减低污染物排放，为企业实现高效优化运行提供理论指导。

Steam power system is the vital and essential energy source of a process industry. Gaseous emission and energy consumption could be high in the energy intensive industries. Model based optimization of steam system is the main technology for saving energy and emission reduction for process industries. The changes of energy structure，materials structure and production planning can cause the performance changes of steam system in certain and uncertain ways, which leads to great difficulties on optimal operation management under certain external conditions and multi-objective considerations. In order to deal with this, the project is to develop a model based multi-objective synthesis and optimization method of steam system considering uncertain conditions. The detailed contents of this research are divided into four items: (1) Prediction and quantitative description of influence on system characteristic by uncertainties, (2) Identification of the major structures and variables in multi-objective problems, (3) developing the mathematical models for multi-objective synthesis and optimization problems,(4) developing the solving method for large multi-objective optimization problems. The operational planning optimization result could present a optimal Parto set for energy saving and emission reduction. Furthermore, the operational planning optimization results could provide a quantitative guidance for the high optimization and intelligent operation of process industries.