Integrated scheduling optimization in the crude-oil refinery industry: from crude-oil unloading to fuel deliveries

Abstract

The integrated scheduling optimization inside the oil-refinery industry is a challenging problem to be solved as it involves decisions concerning logistics and storage of crude-oil feedstocks and product fuels as well as the processing in the refinery network. Approaches to promote the integration of these multi-entity, multi-activity and multi-resource decision-making problems requires good modeling and efficient solving capabilities recognizing the difficulties posed given its logistics and quality aspects. Modeling of these types of processes reliably and accurately is difficult due to the complexities and uncertainties in the feed quality, operating conditions, process measurements, etc. Hitherto, previous literature on the topic of crude-oil scheduling optimization covered the scheduling only from the crude-oil unloading and storage up to the distillation straight-run streams. This research proposal is to extend the scope of the crude-oil scheduling optimization from the crude-oil deliveries through to the product liftings via the refinery process-shop by using closed-loop, on-line and routine process feedback data from the field and laboratory measurements, for better process-shop predictions, integrated with the scheduling cycle. Models for cutpoint optimization of distillates in crude-oil distillation towers is intended in the research. The modeling platform in use to solve the scheduling problem in crude-oil refineries is the IMPL (Industrial Modeling and Programming Language), given its solution of industrial-sized and highly complex problems. (AU)