分隔壁精馏塔分离松节油中蒎烯的多目标优化  

Multi-objective optimization of dividing wall column for separating pinene from turpentine

作　　者：张龙[1] 阮奇[1] 吴开金[2] 严佐毅[1] 许芦杭 李峰 

机构地区：[1]福州大学化学化工学院,福建福州350108 [2]福建省林业科学研究院,福建福州350012 [3]中石化森美(福建)石油有限公司,福建福州350003

出　　处：《计算机与应用化学》2014年第8期902-908,共7页Computers and Applied Chemistry

基　　金：福建省林业厅科研资助项目(闽林科[2011]3号);省级大学生创新训练计划资助项目(201310386036)

摘　　要：为了降低能耗,提高经济效益,在AspenPlus平台上建立了分隔壁精馏塔(DWC)分离松节油中蒎烯的四塔等效模拟流程,采用灵敏度分析确定了对能耗和分离效果影响较大的设计变量及其取值范围,以预分离塔塔板数、主塔塔板数以及能耗最小为目标,建立了DWC分离松节油中蒎烯的多目标优化模型,并利用约束多目标微粒群优化(CMOPSO)算法对模型进行了求解。结果表明:CMOPSO算法能很好地解得DWC的Pareto最优解集,为决策者提供了多种可供选择的DWC优化设计方案;经多目标优化后,在总塔板数(或设备投资费)相近时,与DWC分离松节油的单目标优化结果相比,多目标优化结果可进一步节能21.7 kW;气、液相分配比是DWC特有的,且非常重要的设计变量,采用的双变量灵敏度分析方法能够比较准确地得到两者的适宜取值范围,优化时在该范围内搜索气、液相分配比可望进一步缩短寻优时间。In order to reduce energy consumption and enhance economic benefit, on the basis of building a simulation process of four columns equivalent model of dividing wall column （DWC） for separating pinene from turpentine by Aspen Plus, and confirming the design variables that influence energy consumption and separation effect strongly, as weU as their search scopes by sensitivity analysis, the multi-objective optimization model of dividing wall column for separating pinene from turpentine was established where the objectives were to minimize the total number of stages in prefractionator and main column as well as the heat duty. Constrained MOPSO （CMOPSO） algorithm was used to solve the multi-objective optimization model. The results indicated that CMOPSO algorithm could obtain good Pareto front of DWC which provided decision makers with a variety of alternative optimization design schemes of DWC. Compared with single objective optimization results, the multi-objective optimization of DWC separation process could further save energy 21.7 kW under the similar total number of stages （or equipment investment cost）. Vapor and liquid split fraction were special and important design variables of DWC, and by the use of bivariate sensitivity analysis, their suitable value ranges were confirmed accurately, which was able to further reduce the searching time when vapor and liquid split fraction values were searched in these ranges.

关 键 词：分隔壁精馏塔 松节油 多目标优化 多目标微粒群优化算法 节能 

分 类 号：TQ018[化学工程] TQ02