多收率约束的催化裂化反再系统改进差分进化操作优化
Operational optimization of fluid catalytic cracking reaction-regeneration system with multi-yield constraints using improved differential evolution algorithm
摘要点击 219  全文点击 216  投稿时间:2018-05-08  修订日期:2018-10-24
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DOI编号  10.7641/CTA.2018.80337
  2019,36(8):1207-1216
中文关键词  催化裂化  进化算法  操作优化  差分进化  协同变异  加强搜索  
英文关键词  catalytic cracking  evolutionary algorithms  operation optimization  differential evolution  coordination mutation  enhanced search
基金项目  国家自然科学基金
学科分类代码  
作者单位邮编
曹蓓 东北大学流程工业综合自动化国家重点实验室 110004
陈庆达 东北大学流程工业综合自动化国家重点实验室 
丁进良 东北大学流程工业综合自动化国家重点实验室 110004
中文摘要
      针对现有催化裂化(fluid catalytic cracking, FCC)装置操作优化中未根据市场需求考虑多产品收率约束的问题,本文提出了一种求解多产品收率约束催化裂化反再系统操作优化的改进差分进化(improved differential evolution, iDE)算法. 首先针对FCC操作优化中约束多和不同操作变量的可行范围差异大的特点, 设计了一种协同交互变异策略产生变异个体, 以提高算法的开发和探索能力; 其次提出了一种具有修复功能的参数自适应策略来更新变异因子和交叉因子. 此外考虑到FCC操作优化具有时效强的特点, 提出了对每一代种群中最好个体实施加强搜索的方法, 以提高算法的收敛速度. 仿真结果表明: 在求解多产品收率的FCC反再系统操作优化问题上, 该算法具有较强的全局寻优能力、鲁棒性以及较快的收敛速度.
英文摘要
      In view of existing operation optimization of fluid catalytic cracking (FCC) reaction-regeneration system has not considered multi-yield constraints of product demand, this paper proposes an improved differential evolution (iDE) algorithm to solve the operation optimization problem with multi-yield constraints in FCC unit. Firstly, considering there are many constraints in the FCC operation optimization, and the feasible ranges of different operating variables varies greatly, the cooperative interaction mutation strategy is designed to generate mutants, improving exploitation and exploration capabilities of the algorithm. Secondly, a parameter adaptation strategy with self-repairing capability is proposed to update crossover probability and scaling factor. Additonally, considering that the quick requirement of the operation optimization in FCC unit, an enhanced search strategy is presented to further exploit the best individual in each generation, enhancing the convergence speed of the iDE algorithm. The simulaiton experiments on solving the operation optimization with multi-yield constraints in FCC unit show that it is superior to the art-of-the-state algorithms in global optimization capability, robustness and convergence.