Modeling and Predictive Control of Carbon Dioxide Removal Unit by Aqueous Alkanolamine

Noree Stirak, Noree (2010) Modeling and Predictive Control of Carbon Dioxide Removal Unit by Aqueous Alkanolamine. [Final Year Project] (Unpublished)

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The objectives of this project are to develop modeling and predictive control for Carbon dioxide removal unit by aqueous alkanolamine, compare its performance with an existing PI controller and to reduce carbon dioxide emission and energy consumption from a gas processing plant. Carbon dioxide removal unit is a plant to remove and eliminate carbon dioxide by aqueous alkanolamine. It absorbs impurities of natural gas; carbon dioxide, mercaptant and hydrogen sulfide. Modeling and Predictive Control is an advance technology which can be used to control and implement in process and overcome the problem. By reducing carbon dioxide and energy consumption, it will also result in the reducing amount of carbon dioxide released to the atmosphere which is the main cause of global warming, corrosion of equipment, pipeline and reduce the heating value of the process. There are 4 methods to complete the project which are step testing, system identification, MPC installation and lastly compare Modeling and predictive control with existing PI control. The performance of MPC and PI are compared by using disturbance rejection method which is shows the performance to achieve and maintain the set point of percentage mole fraction of CO2 and main stage temperature at tray no.17. Modeling and Predictive control is a better performance than PI control according to its performance to achieve and maintain at a set point. Consequently, develop Modeling and Predictive Control in amine adsorption technology helps the process to reduce carbon dioxide emissions of natural gas manufacturer and minimize energy use of reboiler duty.

Item Type: Final Year Project
Subjects: T Technology > TP Chemical technology
Departments / MOR / COE: Engineering > Chemical
Depositing User: Users 5 not found.
Date Deposited: 03 Nov 2011 11:23
Last Modified: 25 Jan 2017 09:43

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