Premium
Optimization of single mixed refrigerant natural gas liquefaction plant with nonlinear programming
Author(s) -
Khan Mohd Shariq,
Lee Sanggyu,
Lee Moonyong
Publication year - 2012
Publication title -
asia‐pacific journal of chemical engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.348
H-Index - 35
eISSN - 1932-2143
pISSN - 1932-2135
DOI - 10.1002/apj.642
Subject(s) - refrigerant , liquefaction , process (computing) , nonlinear system , nonlinear programming , natural gas , liquefied natural gas , process engineering , work (physics) , energy (signal processing) , computer science , gas compressor , engineering , mechanical engineering , mathematics , waste management , statistics , geotechnical engineering , physics , quantum mechanics , operating system
The liquefaction of natural gas (NG) in a mixed refrigerant (MR) system is an energy‐demanding process. Much energy is wasted because of its irreversibilities and its nonoptimal execution. The most important factors affecting this process's performance are the refrigerant's composition and flow rate, the suction and evaporation pressures, and the extent of refrigerant vaporization. They should be adjusted to optimize the overall operation. The adjustment of one of these variables will affect the other because of their highly nonlinear interactions. This work reports the optimization of a single MR (SMR) process of NG liquefaction. The SMR process was modeled in the UniSim Design commercial process plant simulator, and the model was optimized for compression energy with nonlinear programming (NLP) while satisfying constraints. The base case for optimization was selected by mesh searching, and case study demonstrates that NLP can reduce energy use and improve the process's efficiency. © 2011 Curtin University of Technology and John Wiley & Sons, Ltd.