作　　者： ; ; ; ; ; ;

机构地区： 中国科学院

出　　处： 《计算机与应用化学》 2010年第8期1059-1062,共4页

摘　　要： 利用流程模拟技术,以UNIQAC为全局热力学模型,设计并严格模拟了一种经由碳酸乙烯脂醇解生产乙二醇(EG)和碳酸二甲酯(DMC)的联产工艺。在此基础上,通过灵敏度分析,建立了基于BP神经网络的多目标模型。该模型以关键塔设备的塔板数和回流比为决策变量,以EC和DMC的纯度为限制变量,以产品收益和能量消耗为目标函数。最后,使用遗传算法NSGAⅡ,实现了该模型的多目标优化。对比优化前后的工艺,发现优化可使工艺总能量消耗降低8.7%,产品收益提高0.9%,同时可显著降低工艺中关键设备的投资。 By using process simulation technology,a process was designed and rigorously modeled to co-produce EG（ethylene glycol） and DMC （dimethyl carbonate） based on UNIQAC as a global thermodynamic model.According to the simulation,a BP artificial neuron network was established in which the stage number and reflux ratio of key column were considered as decision variable,purities of DMC and EG as constraint variable and the whole energy consumption and product profit as objective function.Finally,the multi-objective model was optimized through using a genetic algorithm named NSGAⅡ.By comparison,it was found that the optimization reduces the energy consumption by 8.7%,improves the product profit by 0.9%,and obviously decreases the investment of the key equipment with a same capacity.

关 键 词： 碳酸二甲酯 乙二醇 多目标优化 节能

领　　域： [化学工程] [化学工程]