Abstract
The present work provides a new methodology for optimising crude oil distillation systems. The proposed approach determines the optimum operating conditions for the crude oil distillation unit, where the objective is maximum net profit, while proposing retrofit modifications for the heat exchanger network (HEN) that allow a feasible operation. To improve product profit, the yields of the most valuable products are increased, while considering product specifications, heat recovery and equipment constraints. An artificial neural network model (ANN) is generated to simulate the distillation unit, while the HEN model consists of a mass and energy balance formulated using principles of graph theory. The novelty of this work lies in the simultaneous consideration of the distillation column and HEN models in the optimisation algorithm, with the focus on profitability. Results show that significant economic improvements can be achieved.
