Multi-objective optimization of two-stage-riser catalytic pyrolysis for optimal trade-off in product distribution

WANG Ping; YANG Chaohe; TIAN Xuemin

doi:10.11949/j.issn.0438-1157.20161595

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Multi-objective optimization of two-stage-riser catalytic pyrolysis for optimal trade-off in product distribution

更新时间：2025-12-10

- Multi-objective optimization of two-stage-riser catalytic pyrolysis for optimal trade-off in product distribution
- CIESC Journal Issue 3, Pages: 941-946(2017)
- 作者机构：
  
  1. 中国石油大学(华东)信息与控制工程学院,山东,青岛,266580
  2. 中国石油大学(华东)重质油国家重点实验室,山东,青岛,266580
- 作者简介：
- 基金信息：
- DOI：10.11949/j.issn.0438-1157.20161595
  CLC： E624
- Online First：05 March 2017，
  
  Published：05 March 2017
- 稿件说明：
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WANG Ping, YANG Chaohe, TIAN Xuemin. Multi-objective optimization of two-stage-riser catalytic pyrolysis for optimal trade-off in product distribution[J]. CIESC Journal, 2017, (3): 941-946.
DOI：

WANG Ping, YANG Chaohe, TIAN Xuemin. Multi-objective optimization of two-stage-riser catalytic pyrolysis for optimal trade-off in product distribution[J]. CIESC Journal, 2017, (3): 941-946. DOI： 10.11949/j.issn.0438-1157.20161595.

摘要

根据两段提升管重油催化裂解过程工艺特点和经济运行要求，基于过程机理模型，考虑多种约束条件，构造了同时最大化丙烯、汽油产量以及最小化干气产量的多目标操作优化问题，并采用标准化法向约束方法求解获得了完整、均匀分布的Pareto最优解。仿真结果表明，多目标优化结果可以定量地描述出丙烯、汽油和干气收率间的最优折中，以及操作变量、约束条件对产品分布的影响，可以为过程优化操作提供指导。

Abstract

Based on process characteristics and operation economic demands of heavy oil catalytic pyrolysis in two-stage riser

a multi-objective optimization model

which attempted to maximize yields of propylene and gasoline as well as to minimize yield of dry gas simultaneously

was developed with consideration of process principle model and various constraints. The model was solved by a standardized normal constraint method to formulate a complete set of uniformly distributed Pareto-optimal solutions. Numerical simulations show that the multi-objective optimization could comprehensively and quantitatively describe optimal trade-off among yields of propylene

gasoline and dry gas

as well as influence of operation variables and constraints on product distribution

which could offer guidelines for optimal operation of TMP process.

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