Abstract: The multiobjective optimization problem of gas fractionation unit was discussed. A steady state model was developed to simulate the gas fractionation unit by using a simulator PROII. The analog data was combined with multiple linear regression theory to identify model parameters of gas fractionation unit and establish its multiobjective optimization model. This study used the energy consumption; production output and product recovery as the objective function of multiobjective optimization. The nondominate sorting genetic algorithm (NSGAII) was used to solve the multiobjective optimization model and get pareto optimal solution sets. The optimization results show that it can increase the production of product and decrease energy consumption and emission of propylene by optimizing the operational conditions. The calculation results prove this algorithm had good feasibility validity and versatility. This optimal method can provide operational device and effective guidance tools in gas fractionation unit and other rectification devices.

Key words: Gas fractionation unit,    ,  Multiobjective optimization,    ,  NSGAII,    ,  Multiple linear regression,    , Operation optimization

摘要： 研究了气体分馏装置的多目标优化问题,通过化工模拟软件PRO飊II模拟气体分馏装置的静态模型, 对其模拟数据进行提取后,结合多元线性回归理论对装置进行模型辨识,建立其多目标优化模型,以装置产品产量与能耗、产品回收与能耗作为目标函数进行多目标优化设计,采用非支配排序遗传算法(NSGA飊II)对多目标优化模型进行求解,得到Pareto最优解集。优化结果表明,在相同的能耗下,可以通过优化操作条件提高装置产品产量和减少丙烯的排放量,从而增加装置产品产量的同时降低能耗。计算结果证明了此方法的可行性、有效性和通用性, 为气体分馏装置以及其他分馏装置的优化设计和操作指导提供了有效的方法。

关键词: 气体分馏装置 , 多目标优化, NSGA-II , 多元线性回归 , 操作优化