(249g) A New Proactive Scheduling Methodology for Front-End Crude Oil and Refinery Operations Under Uncertainty of Shipping Delay

Since 1950s, mathematical programming has been implemented in long-term decision making for crude planning to optimize both production and crude purchasing plan. Crude planning and scheduling is very important to a petroleum refinery due to the potential realization of large cost savings. It has been studied and practiced for a long time, especially in the last two decades driven by increasingly intensive global competitions, more volatile feedstock and product markets, as well as stricter environmental regulations. It is not easy task due to the domino effects with the crude flows from upstream to downstream units and the differences between their densities, sulfur contents, product yields etc. 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 activities and cause the originally well set schedule operations suboptimal or even infeasible.

In this paper, a new proactive large-scale continuous scheduling model has been developed for crude unloading, transferring, and processing (which we called CUTP) system to simulate and optimize the front-end and refinery crude-oil operations simultaneously. 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 general objective of the proposed CUTP scheduling methodology is to maximize the total operational profit; meanwhile, it should meet inventory and production demands, and try to maintain refinery plantâ??s normal operations under uncertainty of shipping delay.

The profit maximization and the production flexibility maximization are generally two contradictory aspects that should be well balanced. After developing a CUTP scheduling model, a CFI model need to be added to quantify the shipping delay tolerance. The upper and lower bounds of the combined flexibility index (CFI) need to be identified. When the modeling solution is identified as feasible and the range of CFI is obtained, then the profit maximization and the customized minimum CFI will be considered simultaneously. This makes the optimization more applicable in terms of having taken into account shipping delay uncertainty. For comparison, the optimization results with and without customized CFI are presented and discussed. OA (outer-approximation) based decomposition method has been employed to obtain the optimal solution of the developed MINLP scheduling model. The efficacy of the proposed rescheduling model has been demonstrated by different case studies. There are three major contributions in this paper: (i) the simultaneous scheduling of front-end crude transfer and refinery processing has been achieved; (ii) RPST has been considered in the CUTP model for seamlessly connecting both front-end crude transfer and refinery processing models; and (iii) uncertainty of shipping delay has been taken into account to avoid refinery shut down events by introducing an inventory-related time flexibility index. Based on these new features, the developed methodology has greatly increases the potential profitability and production flexibility of refineries.