Abstract
The solvent deasphalting (SDA) process is specifically designed to selectively remove asphaltene from heavy oil feedstocks. However, high energy consumption resulting from the separation processes used to recover the extraction solvent from the mixture of oil products and solvent is a challenge in the SDA process. In this study, a novel SDA process in which the solvent recovery steps were modified by employing carbon dioxide instead of steam as the stripping agent was developed. In addition, the operating and heat integration parameters of the novel CO2-assisted SDA process were optimized using bilevel optimization to minimize the total annualized cost. A genetic algorithm was applied to optimize the process operating variables in the upper-level problem, including the temperature and pressure of solvent recovery units. In the lower-level problem, heat integration parameters—the minimum temperature difference (ΔTmin) and the heat load distribution of hot and cold utilities—were optimized. The optimization results demonstrated that the novel SDA process is more energy-efficient and economical than the conventional SDA process.
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