Crude Scheduling Research Articles

A novel MINLP model of front-end crude scheduling for refinery with consideration of inherent upset minimization

In this paper, a new methodology has been developed to deal with the front-end crude scheduling (FECS) problems with the consideration of inherent upset minimization (IUM). Specifically, the primary and secondary inherent upsets (IUs) have been defined and modeled to, respectively, address flowrate fluctuations of feeding crude distillation units and the long-distance pipeline (LDPL). Based on such IU characterizations, a new MINLP model with the unit-based continuous time representation is developed to determine the optimal FECS solution by minimizing the overall operating cost and instability along the entire scheduling time horizon. In addition to the IUM, another two merits are also included in this study: (i) the trans-mixing (TM) issue along with crude transportation inside the LDPL has been modeled; (ii) multiple types of crudes with multiple key properties have been simultaneously considered. The developed FECS MINLP model is solved by the ANTIGONE solver to obtain the global optima. The efficacy of the proposed methodology and the FECS model, and the effect of IUM have been investigated through various case studies.

Refinery continuous-time crude scheduling with consideration of long-distance pipeline transportation

In reality, crudes from unloading storage tanks at a docking berth may experience long-distance pipeline transportation to refinery charging tanks before their processing by crude distillation units. Such pipeline transportations cause significant transport delay and crude holdup that will substantially affect plant production performance. Unfortunately, current short-term crude scheduling studies have never systematically considered these issues. In this work, a new continuous-time crude scheduling model has been developed, which addresses the long-distance pipeline transportation and other realistic considerations such as brine settling and multiple jetties for crude unloading. The feeding of crudes into pipeline, and crude movements inside pipeline, as well as crude discharging to the receiving charging tanks are combined with the continuous time formulation of crude scheduling. The efficacy of the developed scheduling model has been demonstrated by three case studies including one industrial size example. An outer-approximation (OA) based iterative algorithm (Karuppiah et al., 2008) is implemented to successfully solve the case studies.

Improving the robustness and efficiency of crude scheduling algorithms

AbstractHigher crude prices have made it even more imperative that refiners blend low‐quality and high‐quality crudes optimally to maximize their margins. Mathematical modeling of crude blending results in bilinear terms, which combined with commonly used feed quality specifications, make crude scheduling a large, nonconvex, mixed‐integer nonlinear optimization problem. The existing literature algorithms and software (DICOPT/GAMS and BARON/GAMS; Brooke et al., GAMS: a user's guide, GAMS, 1998) fail to solve practical instances of this difficult and useful problem. In this paper, we first enhance the practical utility of our previous crude scheduling algorithm by adding 15 properties and corresponding linearly additive indices, which are used in the refinery industry to ensure feed quality. Then, we propose some new iterative strategies to improve the robustness and solution quality of this algorithm. We also propose a partial relaxation strategy to increase its solution speed. We prove its enhanced performance using 24 industry‐scale examples, and estimate bounds on solution quality. In contrast to existing algorithms or software that fail to solve most of these problems, our revised algorithm solves all problems successfully and gives profits within 6% of our computed upper bounds. © 2007 American Institute of Chemical Engineers AIChE J, 2007