Multi-Objective Collaborative Optimization of Distillation Column Group Based on System Identification

被引：0
|
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
来源：
PROCESSES | 2023年 / 11卷 / 02期
基金：
中国国家自然科学基金;
关键词：
multi-objective optimization; ethylene; propylene; clustering; distillation column group; SEPARATION PROCESS; ENERGY SYSTEM; ALGORITHM;
D O I：
10.3390/pr11020436
中图分类号：
TQ [化学工业];
学科分类号：
0817 ;
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.
引用
收藏
页数：14
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