Hybrid model for optimization of crude oil distillation units

Abstract

Planning, scheduling, and real time optimization are currently implemented using different types of models, which causes discrepancies between their results. This work presents a single model of a crude distillation unit (preflash, atmospheric, and vacuum towers) suitable for all of these applications, thereby eliminating discrepancies between models used in these decision processes. Product true boiling point (TBP) curves are predicted via partial least squares model from the feed TBP curve and operating conditions (flows, pumparound heat duties, furnace coil outlet temperatures). Combined with volumetric and energy balances, this enables prediction of crude distillation on par with a rigorous distillation model, with 0.5% root mean square error (RMSE) over a wide range of conditions. Associated properties (e.g., gravity, sulfur) are computed for each product based on its distillation curve and corresponding property distribution in the feed. Model structure makes it particularly amenable for development from plant data. © 2015 American Institute of Chemical Engineers AIChE J, 62: 1065–1078, 2016