Optimization and design of a new column sequencing for crude oil distillation at Basrah refinery

Abstract

The utilization of distillation stands as a predominant separation method within the chemical and petroleum industries, prominently influencing operational costs and environmental impact due to energy consumption. Enhancing energy efficiency holds paramount significance in elevating the sustainability and overall efficacy of distillation operations. Within this study, we introduce an innovative approach termed “marginal vapor flow (MVF)” to optimize the distillation column sequence for crude oil processing, focusing on the third distillation unit at the Basra Refinery. This research evaluates diverse column designs through streamlined simulations using Aspen HYSYS V11 software. The study determines total energy consumption as a benchmark, comparing it against the optimal sequence recommended by the MVF methodology. A novel application of the downward reduction equation to crude oil guides the selection of light and heavy components. Key findings from this comprehensive analysis showcase the potency of combining MVF with Aspen HYSYS for optimizing crude oil distillation column sequences. Aspen HYSYS, a widely recognized process simulation tool, accurately represents distillation processes. Simultaneously, MVF facilitates the determination of optimal column sequences based on marginal vapor flow rates. Notably, the results reveal that within the studied sequences, sequence 9 exhibits the lowest total MVF of (1393.4 kmol/h), signifying its optimality, while sequence 2 displays the highest total MVF of (4827.3 kmol/h), representing the least favorable scenario. Simulation of the optimal sequence derived through the MVF approach exhibits a remarkable 35% reduction in energy consumption compared to real-life operations. Conversely, simulating the least favorable sequence demonstrates a substantial 32% increase in energy consumption compared to actual operations. This study underscores the pivotal role of MVF methodology in optimizing distillation sequences for enhanced energy efficiency, providing actionable insights for refining operations to significantly reduce energy consumption and operational costs while advancing sustainability goals.