A nonlinear programming model for refinery planning and optimisation with rigorous process models and product quality specifications

The yield of products in large-scale plants such as oil refineries have a significant impact on overall profitability. Currently, many refineries apply Linear Programming (LP) techniques for their production planning models. However, this will often give inconsistent predictions of refinery productivity and operation. Moreover, the stringent environmental regulations, product qualities, and heavier feed stocks make it necessary to develop accurate models for refinery-production planning. In this work, an approach with more accurate representation of the refinery processes is presented. The resulting model is able to predict the operating variables such as the Crude Distillation Unit (CDU) cut-point temperatures and the conversion of the Fluid Catalytic Cracking unit (FCC). It can also evaluate properties of the final products to meet the market specification as well as the required product demands to achieve a maximum refinery profit. The model is illustrated on representative case studies, and the results are discussed. [Received: December 4, 2007; Accepted: January 17, 2008]