This paper is the third of a three-part series that applies optimization to maximize the productivity and minimize operating costs of heat-integrated crude oil distillation systems. The approach presented in this paper implements simulation models for the distillation process and heat exchanger network (HEN), and HEN retrofit models into the overall optimization framework. The optimization approach is formulated in two levels. In the first level, simulated annealing is used to optimize the operating conditions of the crude oil distillation unit (e.g., distillation products and stripping steam flow rates, pump-around duties and temperature drops, and furnace exit temperatures) and to propose HEN structural modifications (e.g., adding, removing, relocating heat exchangers; adding, removing stream splitters, etc.). The second level is a nonlinear least-squares problem used to enforce HEN constraints. Three case studies illustrate the application of this approach to increase net profit and reduce annualized costs.
FingerprintDive into the research topics of 'Optimization of Heat-Integrated Crude Oil Distillation Systems. Part III: Optimization Framework'. Together they form a unique fingerprint.
Increasing productivity in the process industries through the use of artificial intelligence and machine learning for the optimisation of distillation operations
Impact: Economic, Environmental