Modeling and optimization of ethylene cracking feedstock scheduling based on P-graph

MU Peng; GU Xiangbai; ZHU Qunxiong

doi:10.11949/j.issn.0438-1157.20181370

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Modeling and optimization of ethylene cracking feedstock scheduling based on P-graph

Process system engineering | 更新时间：2026-07-24

- Modeling and optimization of ethylene cracking feedstock scheduling based on P-graph
- CIESC Journal Vol. 70, Issue 2, Pages: 556-563(2019)
- 作者机构：
  
  北京化工大学信息科学与技术学院，北京 100029
- 作者简介：
- 基金信息：
- DOI：10.11949/j.issn.0438-1157.20181370
  CLC： TQ 021.8
- Received：18 November 2018，
  
  Revised：2018-12-11，
  
  Online First：16 June 2020，
  
  Published：05 February 2019
- 稿件说明：
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牟鹏, 顾祥柏, 朱群雄. 基于P-graph的乙烯裂解原料调度建模与优化[J]. 化工学报, 2019, 70(2): 556-563

MU Peng, GU Xiangbai, ZHU Qunxiong. Modeling and optimization of ethylene cracking feedstock scheduling based on P-graph[J]. CIESC Journal, 2019, 70(2): 556-563
牟鹏, 顾祥柏, 朱群雄. 基于P-graph的乙烯裂解原料调度建模与优化[J]. 化工学报, 2019, 70(2): 556-563 DOI： 10.11949/j.issn.0438-1157.20181370.

MU Peng, GU Xiangbai, ZHU Qunxiong. Modeling and optimization of ethylene cracking feedstock scheduling based on P-graph[J]. CIESC Journal, 2019, 70(2): 556-563 DOI： 10.11949/j.issn.0438-1157.20181370.

摘要

乙烯工业不同的裂解装置间存在着设备、技术上的差别，每一种原料在乙烯工厂不同炉型或工艺的裂解装置的乙烯产品收率、能耗也存在着差别。随着新的乙烯工厂的投产，需要同时运行台数众多的差异化裂解装置，从而为通过优化调度乙烯裂解原料实现提高物效、降低能耗提供了空间。对于此类工厂间原料调度及能耗优化问题提出了一种基于P-graph的建模和优化方法(scheduling generation based on P-graph

SGBP算法)，该算法通过P-graph本身提取过程结构信息的能力，在加速求解的同时，保留了次优解集。之后以两个实际的乙烯厂为研究实例，采用提出的SGBP方法实现了原料调度的建模和优化，该方法与MINLP优化算法的对比分析验证了提出方法的优势：(1)可以同时提供较为丰富的最优解与次优解方案；(2)提出方法的最优结果与MINLP的优化效果相当；(3)优化后的整体能耗下降明显，为生产计划人员选择可采用灵活的原料调配方案提供了多种可选择的运行方案。

Abstract

There are differences in equipment and technology between different cracking devices in the ethylene industry. There is also a difference in the yield and energy consumption of ethylene products from cracking devices of different furnace types or processes in each ethylene feedstock plant. With the commissioning and starting of the new ethylene plant

it is necessary to simultaneously operate a large number of differential cracking devices

thereby providing space for the optimization of ethylene cracking raw materials to achieve improved material efficiency and lower energy consumption. This paper proposes a modeling and optimization method based on P-graph for the scheduling of raw materials and energy optimization among such plants(SGBP). This algorithm extracts the structural information of the process by P-graph itself

and preserves the suboptimal solution set w

hile accelerating the solution. Afterwards

using a certain ethylene plant as an example

the proposed method was applied to achieve the modeling and optimization of raw material scheduling. The advantages of the proposed method has been verified

via

comparing with MINLP and one kind of intelligent optimization algorithm. It can provide simultaneously more abundant optimal solution and suboptimal solution. The optimal result of the proposed method is equivalent to the optimization effect of MINLP. The overall energy consumption after optimization is significantly reduced

and a variety of alternative operation options can be provided for the production plan personnel to choose flexible raw material deployment plans.

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