文献类型：期刊文献

英文题名：Multi-Objective Collaborative Optimization of Distillation Column Group Based on System Identification

作者：He, Renchu[1,2];Ju, Keshuai[1];Li, Linlin[3];Long, Jian[1]

机构：[1]East China Univ Sci & Technol, Key Lab Smart Mfg Energy Chem Proc, Minist Educ, Shanghai 200237, Peoples R China;[2]East China Univ Sci & Technol, Engn Res Ctr Proc Syst Engn, Minist Educ, Shanghai 200237, Peoples R China;[3]Univ Sci & Technol Beijing, Sch Automat & Elect Engn, Beijing 100083, Peoples R China

年份：2023

卷号：11

期号：2

外文期刊名：PROCESSES

收录：;EI(收录号：20241515855929);WOS:【SCI-EXPANDED(收录号:WOS:000942284300001)】；

基金：This work was supported by National Key Research and Development Program of China (2022YFB3305901), National Natural Science Foundation of China (62073142, 62136003, 61973124), Fundamental Research Funds for the Central Universities and the Programme of Introducing Talents of Discipline to Universities (the 111 Project) under Grant B17017.

语种：英文

外文关键词：multi-objective optimization; ethylene; propylene; clustering; distillation column group

摘要：In this paper, a multi-objective collaborative optimization (MOCO) strategy is proposed for making decisions on a distillation column group. Firstly, based on data preprocessing, the operating modes of the tower group are determined by use of the fuzzy C-means clustering method. Secondly, based on the proposed concept of a collaborative variable, the discrete state-space model of the main towers are constructed by the subspace identification method. Then, a MOCO optimization model is designed for the ethylene plant. Finally, NSGA-III is used to solve the optimization problem. An analysis of a Pareto-optimal frontier and population is carried out. To illustrate the superiority of the proposed strategy, the results are compared with historical data and the appealing operation area is finally obtained.