文献类型：期刊文献

英文题名：Integrated Operation and Cyclic Scheduling Optimization for an Ethylene Cracking Furnaces System

作者：Jin, Yangkun[1,2];Li, Jinlong[1,2];Du, Wenli[1,2];Qian, Feng[1,2]

机构：[1]E China Univ Sci & Technol, Minist Educ, Key Lab Adv Control & Optimizat Chem Proc, Shanghai 200237, Peoples R China;[2]E China Univ Sci & Technol, Sch Informat Sci & Engn, Shanghai 200237, Peoples R China

年份：2015

卷号：54

期号：15

起止页码：3844

外文期刊名：INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH

收录：;EI(收录号：20151800806533);WOS:【SCI-EXPANDED(收录号:WOS:000353929300013)】；

基金：This work is supported by Major State Basic Research Development Program of China (2012CB720500), National Natural Science Foundation of China (U1162202, 21276078), Shanghai R&D Platform Construction Program (13DZ2295300), and Natural Science Foundation of Shanghai (13ZR1411300).

语种：英文

外文关键词：Furnaces - Problem solving - Scheduling - Nonlinear programming - Cracks - Catalytic cracking - Integer programming

摘要：Multiple cracking furnaces in an ethylene plant tun in parallel to produce ethylene, propylene, and other products from different hydrocarbon feedstocks. Because both coke formation in radiant coils and change of operation Conditions with time have significant effects on the performance of cracking furnaces, it is better for the cyclic scheduling to be simultaneously optimized with the operation conditions. To match this real requirement, a mixed-integer dynamic optimization (MIDO) problem is presented for the optimization of both operation conditions and cyclic scheduling simultaneously, through which the optimal assignment, the processing time, the subcycle number, and the optimal operation conditions of different feeds in different cracking furnaces are determined at the same time. To solve the MID problem, it is discretized and converted into a large scale mixed-integer nonlinear programming (MINLP) problem. The two scheduling cases of a cracking furnaces system are illustrated showing a remarkable increase in the economic performance as compared with that of the traditional Method.