文献类型：期刊文献

英文题名：Simultaneous Optimization and Heat Integration of an Aromatics Complex with a Surrogate Model

作者：Liu, Yurong[1];Yang, Minglei[1];Zhao, Liang[1];Du, Wenli[1];Zhong, Weimin[1];Qian, Feng[1]

机构：[1]East China Univ Sci & Technol, Key Lab Adv Control & Optimizat Chem Proc, Minist Educ, Shanghai 200237, Peoples R China

年份：2021

卷号：60

期号：9

起止页码：3633

外文期刊名：INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH

收录：;EI(收录号：20211410179576);WOS:【SCI-EXPANDED(收录号:WOS:000629059100015)】；

基金：This work was supported by the National Natural Science Foundation of China (Basic Science Center Program, 61988101), International (Regional) Cooperation and Exchange Project (61720106008), National Natural Science Foundation of China (61873093), and National Natural Science Fund for Distinguished Young Scholars (61725301).

语种：英文

外文关键词：Neural networks - Distillation - Complex networks - Heat exchangers - Aromatization

摘要：The aromatics complex is essential in the production of p-xylene and contains several distillation towers and reactors, making this process highly energy intensive. To save energy for the aromatics complex, a novel framework for optimizing the process and heat exchanger network simultaneously is presented. Two models are included in this framework, namely, the process model, which is established through artificial neural networks, and the heat exchanger network model, which includes streams with phase changes. In addition, a disjunctive formulation is proposed to diagnose the process streams with or without latent heat according to the operating conditions. The performance of the proposed approach is illustrated with two case studies. The results demonstrate the significant potential in energy savings and considerable increase in the profit of the whole system.