443829 A New Reactive Scheduling Methodology for Front End Crude Oil and Refinery Operations Under Uncertainty of Shipping Delay

Tuesday, April 12, 2016: 10:59 AM
336B (Hilton Americas - Houston)
Jialin Xu, Shujing Zhang, Jian Zhang and Qiang Xu, Dan F. Smith Department of Chemical Engineering, Lamar University, Beaumont, TX

Scheduling and planning of crude oil is very important to a petroleum refinery due to the potential realization of large cost savings and also the one of most challenging problems for refinery operations.  However, it is not easy to simulate and optimize the front-end crude-oil and refinery operations at the same time. And in reality, the crude scheduling activities are highly vulnerable to disruptions brought by various uncertainties. For example, the shipping delay may disrupt the associated tank loading or unloading activities and cause the originally well set schedule operations suboptimal or even infeasible. 

In this paper, a new reactive two-stage scheduling methodology for front-end crude oil and refinery operations has been developed to manage crude movements from ship unloading to refinery processing under uncertainty of shipping delay. The scope of the scheduling problem includes crude oil unloading from vessels to storage tanks at onshore berths, transfer of crude from these tanks to charging tanks, charging crude distillation units and further processing of crude inside the refinery, which includes crude distillation, cracking, coking, reforming, hydrotreating, product blending and component recovery.

The objective of the proposed scheduling methodology is to maximize the total operational profit; meanwhile, it should meet inventory and production demands, and try to maintain refinery plant’s normal operations under uncertainty of shipping delay. The scheduling model is a large-scale mixed integer nonlinear programming problem (MINLP). The efficacy of the proposed rescheduling model has been demonstrated by different case studies.

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See more of this Session: Decision-Making for Industrial Process Systems II
See more of this Group/Topical: Computing and Systems Technology Division