Data-driven modeling and global optimization of industrial-scale petrochemical planning operations

Fani Boukouvala, Jie Li, Xin Xiao, Christodoulos A. Floudas

    Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

    Abstract

    In this work, we have developed a data-driven
    model which is used for the optimization of planning operations
    of a large petrochemical complex, comprising of a petrochemical
    plant and two ethylene plants. We have developed unit operation
    models for all of the processes present within the industrial
    superstructure, which are integrated with mass-balance,
    property specification, demand, capacity and unit selection
    constraints, to form the overall planning problem. The models in
    this formulation contain parameters which are automatically
    fitted based on the data obtained from the operation of the plant
    units. For the dynamic updating of the model parameters, we
    have developed a user-friendly computational platform which
    allows the input of new operational data as well as cost, price,
    demand and specification information for the planning period of
    interest. Once the parameters are updated and the predictive
    ability of the models is confirmed, the formed mixed integer
    nonlinear optimization problem is solved to global optimality,
    providing the globally optimal flowrates and operating modes
    which maximize the profit, while simultaneously satisfying
    specification and demand constraints. Using the developed
    framework, we have obtained results for multiple case studies
    proving that the obtained solutions lead to significant
    improvements in profit when compared to historically applied
    operating plans.
    Original languageEnglish
    Title of host publicationData-driven modeling and global optimization of industrial-scale petrochemical planning operations
    PublisherAmerican Automatic Control Council
    Pages3340-3345
    ISBN (Print)978-1-4673-8682-1
    Publication statusPublished - 2016

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