基于原油TBP曲线校正的常减压装置操作的多目标优化  

Multi-objective optimization of atmospheric and vacuum distillation unit operation based on correction of oil TBP curve

作　　者：陶勇[1] 熊佐松 刘海燕[1] 鄢烈祥[1] 廖安[1] 

机构地区：[1]武汉理工大学化学工程学院,湖北武汉430070 [2]中国石油化工股份有限公司武汉石化分公司,湖北武汉430082

出　　处：《计算机与应用化学》2014年第3期311-315,共5页Computers and Applied Chemistry

基　　金：国家自然科学基金资助项目(21376185)

摘　　要：常减压装置的模拟与优化的效果取决于原油的实沸点(TBP)数据,针对进料原油物性时常变化,且实沸点(TBP)数据(曲线)测定费时和成本高的情况,提出了一种校正原油TBP曲线的方法。该方法以各侧线产品干点的模拟值与工况值误差平方和最小为目标,将TBP曲线的校正转化为最优化问题来求解。采用该方法能使模拟的精度显著提高。在此基础上,以汽提蒸汽量、侧线采出量、中段回流量为操作变量,以常压塔的拔出率最大化和能耗最小化为优化目标,建立了常减压装置的多目标优化模型。应用带精英策略的非支配遗传算法(NSGA-Ⅱ)对常减压装置进行优化求解,得到了常压塔总收率-能耗的最优Pareto解集,为常减压装置的操作优化提供了依据。The effectiveness of simulation and optimization of atmospheric and vacuum distillation unit depends on oil TBP data. An correction method for oil TBP curve is proposed towards the changeable quality of feed oil, time-consuming and high-cost of oil TBP curve measurement. The optimization objective of minimizing quadratic sum error between simulation value and operating conditions is performed instead of TBP curve correction. The accuracy of simulation is significantly improved by this method. On this basis, taking stripping steam, stripper production and mid-pumparound as operating variables, and taking maximum of atmospheric distillation column yield and minimum of energy consumption as optimization objectives, multi-objective optimization model of atmospheric and vacuum distillation is established. The Pareto front of atmospheric distillation column yield ＆ energy consumption is obtained by Non-dominated sorting genetic algorithm with elitist strategy （NSGA-II）, which provides a theoretical basis for process optimization.

关 键 词：常减压装置 TBP曲线校正 多目标优化 NSGA—II 

分 类 号：TP13[自动化与计算机技术—控制理论与控制工程]