Procurement planning in oil refining industries considering blending operations

Thordis Anna Oddsdottir, Martin Grunow, Renzo Akkerman

    Research output: Contribution to journalJournal articleResearchpeer-review

    Abstract

    This paper addresses procurement planning in oil refining, which has until now only had limited attention in the literature. We introduce a mixed integer nonlinear programming (MINLP) model and develop a novel two-stage solution approach, which aims at computational efficiency while addressing the problems due to discrepancies between a non-linear and a linearized formulation. The proposed model covers realistic settings by allowing the blending of crude oil in storage tanks, by modeling storage tanks and relevant processing units individually, and by handling more crude oil types and quality parameters than in previous literature. The developed approach is tested using historical data from Statoil A/S as well as through a comprehensive numerical analysis. The approach generates a feasible procurement plan within acceptable computation time, is able to quickly adjust an existing plan to take advantage of individual procurement opportunities, and can be used within a rolling time horizon scheme. © 2013 Elsevier Ltd.
    Original languageEnglish
    JournalComputers and Chemical Engineering
    Volume58
    Pages (from-to)1-13
    ISSN0098-1354
    DOIs
    Publication statusPublished - 2013

    Keywords

    • Blending
    • Crude oil
    • Decision support systems
    • Digital storage
    • Nonlinear programming
    • Refining
    • Tanks (containers)
    • Petroleum refining
    • Procurement planning
    • Oil refining industry
    • Mixed integer non-linear programming
    • Solution approach
    • Crude oil scheduling
    • Decision support

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