Refinery scheduling of crude oil unloading, storage and processing using a model predictive control strategy

A model predictive control (MPC) strategy is presented to determine the optimal control decisions for the short-term refinery scheduling problem. For cases where process disturbances occur or new plans need to be implemented during the scheduling period, the moving horizon strategy allows control decisions to be updated effectively to maintain an optimal operation. Furthermore, this strategy takes advantage of information regarding the system and disturbance prediction over the moving horizon to be used in obtaining the control decisions for the given time interval. To demonstrate the performance of the MPC strategy, especially for various moving horizon lengths, three different case studies concerning scheduling problem in a crude oil refinery were used. The refinery includes the shipping vessels, the storage and charging tanks, and the crude distillation units. Several disturbance scenarios regarding mixed oil demands were constructed to illustrate the performance of the proposed strategy.