Please use this identifier to cite or link to this item: https://doi.org/10.1016/j.apenergy.2013.06.010
Title: Knowledge based decision making method for the selection of mixed refrigerant systems for energy efficient LNG processes
Authors: Khan, M.S.
Lee, S.
Rangaiah, G.P. 
Lee, M.
Keywords: Energy optimization
Exergy analysis
LNG plant
Mixed refrigerant system
Natural gas liquefaction
Process knowledge based optimization
Issue Date: Nov-2013
Citation: Khan, M.S., Lee, S., Rangaiah, G.P., Lee, M. (2013-11). Knowledge based decision making method for the selection of mixed refrigerant systems for energy efficient LNG processes. Applied Energy 111 : 1018-1031. ScholarBank@NUS Repository. https://doi.org/10.1016/j.apenergy.2013.06.010
Abstract: Mixed refrigerant (MR) systems are used in many industrial applications because of their high energy efficiency, compact design and energy-efficient heat transfer compared to other processes operating with pure refrigerants. The performance of MR systems depends strongly on the optimum refrigerant composition, which is difficult to obtain. This paper proposes a simple and practical method for selecting the appropriate refrigerant composition, which was inspired by (i) knowledge of the boiling point difference in MR components, and (ii) their specific refrigeration effect in bringing a MR system close to reversible operation. A feasibility plot and composite curves were used for full enforcement of the approach temperature. The proposed knowledge-based optimization approach was described and applied to a single MR and a propane precooled MR system for natural gas liquefaction. Maximization of the heat exchanger exergy efficiency was considered as the optimization objective to achieve an energy efficient design goal. Several case studies on single MR and propane precooled MR processes were performed to show the effectiveness of the proposed method. The application of the proposed method is not restricted to liquefiers, and can be applied to any refrigerator and cryogenic cooler where a MR is involved. © 2013 Elsevier Ltd.
Source Title: Applied Energy
URI: http://scholarbank.nus.edu.sg/handle/10635/89309
ISSN: 03062619
DOI: 10.1016/j.apenergy.2013.06.010
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