%0 Journal Article
%T 基于遗传算法的常减压装置多目标优化
%A 黄小侨
%A 李娜
%A 李军
%A 宋丽娟
%A 张玉贞
%A 段永生
%J 中国石油大学学报(自然科学版)
%D 2016
%R 10.3969/j.issn.1673-5005.2016.02.021
%X 利用流程模拟软件Aspen Plus建立常减压装置稳态模型,以经济效益和CO2排放量为目标,提出基于遗传算法NSGA-Ⅱ的优化方法,利用该方法求解常减压装置多目标优化问题,从而得到一组最优混炼比和操作条件的Pareto解集。结果表明,在保证产品规格的前提下,经济效益和CO2排放量呈正比;增大轻油比例可以提高经济效益,但也必然会导致CO2排放量的增大。</br>A steady state model was developed to simulate an industrial crude distillation unit by using a process simulator Aspen Plus. On the basis of the genetic algorithm NSGA-Ⅱ, the optimization approach was proposed in terms of economic benefit and CO2 emission, through which the multi-objective optimization problem of the crude unit was solved. And the Pareto-optimal solutions of the optimal blending ratio and operational parameters were obtained. The results show that the economic benefit is proportional to the growing of CO2 emissions on the premise of keeping the product specification on the base of distribution of Pareto front. Therefore, increasing the proportion of light oil can improve economic profit and lead to increased CO2 emissions inevitably
%K 常减压 Aspen Plus软件 多目标优化 Pareto解集 混炼比&lt
%K /br&gt
%K crude distillation unit Aspen Plus software multi-objective optimization Pareto front crude oil blending ratio
%U http://zkjournal.upc.edu.cn/zgsydxxb/ch/reader/view_abstract.aspx?file_no=20160221&flag=1