Petroleum refinery scheduling with consideration for uncertainty

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dc.contributor.advisor Cao, Yi
dc.contributor.advisor Kokossis, Antonis Hamisu, Aminu Alhaji 2015-09-09T13:30:00Z 2015-09-09T13:30:00Z 2015-07
dc.description.abstract Scheduling refinery operation promises a big cut in logistics cost, maximizes efficiency, organizes allocation of material and resources, and ensures that production meets targets set by planning team. Obtaining accurate and reliable schedules for execution in refinery plants under different scenarios has been a serious challenge. This research was undertaken with the aim to develop robust methodologies and solution procedures to address refinery scheduling problems with uncertainties in process parameters. The research goal was achieved by first developing a methodology for short-term crude oil unloading and transfer, as an extension to a scheduling model reported by Lee et al. (1996). The extended model considers real life technical issues not captured in the original model and has shown to be more reliable through case studies. Uncertainties due to disruptive events and low inventory at the end of scheduling horizon were addressed. With the extended model, crude oil scheduling problem was formulated under receding horizon control framework to address demand uncertainty. This work proposed a strategy called fixed end horizon whose efficiency in terms of performance was investigated and found out to be better in comparison with an existing approach. In the main refinery production area, a novel scheduling model was developed. A large scale refinery problem was used as a case study to test the model with scheduling horizon discretized into a number of time periods of variable length. An equivalent formulation with equal interval lengths was also presented and compared with the variable length formulation. The results obtained clearly show the advantage of using variable timing. A methodology under self-optimizing control (SOC) framework was then developed to address uncertainty in problems involving mixed integer formulation. Through case study and scenarios, the approach has proven to be efficient in dealing with uncertainty in crude oil composition. en_UK
dc.language.iso en en_UK
dc.publisher Cranfield University en_UK
dc.rights © Cranfield University 2015. All rights reserved. No part of this publication may be reproduced without the written permission of the copyright owner. en_UK
dc.subject Refinery optimization en_UK
dc.subject mixed integer programming en_UK
dc.subject modelling en_UK
dc.subject receding horizon en_UK
dc.subject self-optimizing control en_UK
dc.title Petroleum refinery scheduling with consideration for uncertainty en_UK
dc.type Thesis or dissertation en_UK
dc.type.qualificationlevel Doctoral en_UK
dc.type.qualificationname PhD en_UK

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