CIESC Journal ›› 2019, Vol. 70 ›› Issue (2): 556-563.DOI: 10.11949/j.issn.0438-1157.20181370

• Process system engineering • Previous Articles     Next Articles

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

Peng MU(),Xiangbai GU,Qunxiong ZHU()   

  1. College of Information Science and Technology, Beijing University of Chemical Technology, Beijing 100029, China
  • Received:2018-11-18 Revised:2018-12-11 Online:2019-02-05 Published:2019-02-05
  • Contact: Qunxiong ZHU

基于P-graph的乙烯裂解原料调度建模与优化

牟鹏(),顾祥柏,朱群雄()   

  1. 北京化工大学信息科学与技术学院,北京 100029
  • 通讯作者: 朱群雄
  • 作者简介:<named-content content-type="corresp-name">牟鹏</named-content>(1991—),男,博士研究生,<email>aileengujy@126.com</email>|朱群雄(1960—),男,博士,教授,<email>zhuqx@mail.buct.edu.cn</email>
  • 基金资助:
    国家自然科学基金重点项目(61533003)

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 while 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.

Key words: ethylene, scheduling, P-graph, optimization, SGBP, systems engineering, process systems

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。

关键词: 乙烯, 调度, P-graph, 优化, SGBP算法, 系统工程, 过程系统

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