Design and Implementation of Inferential (IQ) Model to Predict i-C4 Percentage and to Save Fuel Gas Consumption in Gas Train De-Propaniser Tower

Authors

  • Mohammed Hegazy

Keywords:

Model-Base Inferential IQ, i-C4 percentage, De-Propaniser, Linest Correlation, DMC uptime, Control Variable (CV), DMCplus, Gain, Inferential Predictive Control.

Abstract

The main goal of this paper is to present the effect of using reflux to feed ratio as an independent variable in designing a Model-Base Inferential IQ to predict the i-C4 percentage in the top of a DE-Propaniser tower. The addition of this variable is a modification of an existing inferential IQ model with a design, which only uses the De-Propaniser tower top temperature and pressure as independent variables, and has resulted in significant improvements in the prediction of i-C4 percentage, operation and economics of the tower operation.

References

Aspen Tech. (Manufacturing Suite).

Kuwait National Petroleum, MAA, Gas Plant operating manual.

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Published

2015-08-04

How to Cite

Hegazy, M. (2015). Design and Implementation of Inferential (IQ) Model to Predict i-C4 Percentage and to Save Fuel Gas Consumption in Gas Train De-Propaniser Tower. International Journal of Sciences: Basic and Applied Research (IJSBAR), 24(1), 156–164. Retrieved from https://gssrr.org/index.php/JournalOfBasicAndApplied/article/view/4431

Issue

Vol. 24 No. 1 (2015)

Section

Articles

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