Author/Authors :
D.J. Dave، نويسنده , , M.Z. Dabhiya، نويسنده , ,
S.V.K. Satyadev، نويسنده , , S. Ganguly and
D.N. Saraf، نويسنده ,
Title Of Article :
Online tuning of a steady state crude
distillation unit model for real time
applications
Latin 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.
NaturalLanguageKeyword :
Online tuning , Crude distillation , Distillation model tuning , Crude TBP backcalculation
JournalTitle :
Studia Iranica