化工学报 ›› 2016, Vol. 67 ›› Issue (12): 5105-5111.DOI: 10.11949/j.issn.0438-1157.20161200

• 过程系统工程 • 上一篇    下一篇

基于装置级优化控制与厂级调度优化集成的过程模型方法

高小永, 江永亨, 黄德先   

  1. 清华大学自动化系, 清华大学信息科学与技术国家实验室, 北京 100084
  • 收稿日期:2016-08-30 修回日期:2016-09-02 出版日期:2016-12-05 发布日期:2016-12-05
  • 通讯作者: 黄德先。huangdx@tsinghua.edu.cn
  • 基金资助:

    国家高技术研究发展计划项目(2013AA040702);国家自然科学基金项目(21276137,61273039)。

Process modelling based on integration of unitwide optimal process control and plantwide scheduling

GAO Xiaoyong, JIANG Yongheng, HUANG Dexian   

  1. Department of Automation, Tsinghua National Laboratory for Information Science and Technology, Tsinghua University, Beijing 100084, China
  • Received:2016-08-30 Revised:2016-09-02 Online:2016-12-05 Published:2016-12-05
  • Supported by:

    supported by the National High Technology Research and Development Program of China(2013AA040702) and the National Natural Science Foundation of China(21276137, 61273039).

摘要:

随着全球化市场竞争日趋激烈,炼油生产过程的系统工程方法引起学术界和工业界的普遍关注。由于炼油生产过程的复杂性,现有方法远未有效解决过程模型准确描述问题,直接导致系统工程应用效果欠佳;过程模型的准确描述成为阻碍过程系统工程成功应用的关键。从困扰过程模型准确描述的症结出发,提出了一种基于装置级优化控制与厂级调度优化集成策略的模型描述方法,意在打破当前装置级底层控制系统和上层过程系统工程应用相互孤立情况下带来的系统间互为排斥、相互抑制的困局。在炼油生产过程装置分类的基础上,基于装置级优化控制的操作运行大数据所蕴含的多个最优操作模态信息,提出分装置类别和分操作模式的多模型描述方法,解决变化原料及操作工况的影响;基于该模型描述机制,将能够为智能炼油提供基础。

关键词: 集成, 系统工程, 过程控制, 大数据, 炼油生产过程, 过程模型描述

Abstract:

The process system engineering methods for refinery production process have drawn increasing concerns in both academic and industrial communities due to the fierce global competition. Due to the complexity of refinery production process, the effective process model is still an open problem, which hampers process system engineering application. In some senses, the process model is the fundamental basis for successful application. To break this bottleneck, an integration between unit-wide optimal process control system and plant-wide scheduling system based modelling framework is proposed. The whole refinery production processes are divided into several different classes, and each class unit has a unique and well-designed model structure. Based on the big operational data collected from the unit-wide optimal control system, the multi-mode models are obtained to take varying crudes and operating conditions into account. This modelling mechanism can provide the concrete model for smart or intelligent refinery.

Key words: integration, system engineering, process control, big data, refinery production process, process model description

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