Online tuning of a steady state crude distillation unit model for real time applications

Abstract The steady state simulators, used for on-line performance prediction and for on-line optimization in crude distillation units are often sensitive to small variations in the feed composition, which is specified in terms of a True Boiling Point (TBP) vs volume percent distilled curve. The exact feed TBP is often not available during the plant operation. Also stratification of raw crude oil into layers in the large tank farm sections cause severe operating problems in terms of the stability of the column. If feed TBP can be predicted online, necessary feedforward action can considerably reduce the operating problems. A model has been developed for backcalculation of feed TBP using measured plant parameters. A heat balance is performed around an envelope encompassing the rectifying section of the fractionator and is followed by the calculation of Equilibrium Flash Vaporization (EFV) temperatures at six different locations of the column which are correlated with corresponding feed TBP temperatures. The second part of model tuning consists of calculating model parameters in the form of point efficiencies so as to minimize the discrepancy between the simulator predicted and measured column parameters which arises out of modelling approximations such as assumption of phase equilibria at each stage and use of imperfect thermodynamics correlations. The simulator results, after tuning, were found to match the plant measurements within two percent in all the cases investigated. The simulator output was used to predict various product properties using a Property Prediction package and these were also found to match well with those of laboratory measurements. Both the backcalculation of feed TBP and the efficiency tuning need to be implemented on-line for inferential control and supervisory optimization.