TY - JOUR
T1 - Safety, economics, environment and energy based criteria towards multi-objective optimization of natural gas sweetening process
T2 - An industrial case study
AU - Tikadar, Debasish
AU - Gujarathi, Ashish M.
AU - Guria, Chandan
N1 - Funding Information:
The initial help from Professor G. P. Rangaiah is gratefully acknowledged. The authors also thank the referees for their helpful comments to improve the quality of the manuscript.
Publisher Copyright:
© 2021
PY - 2021/11
Y1 - 2021/11
N2 - In this study, multi-objective optimization of the methyl di-ethanolamine-based industrial natural gas sweetening process is carried out using the improved multi-objective differential evolutionary algorithm for the enhancement of the plant performance by tuning the critical process parameters. Due to the involvement of conflicting objectives, i.e., minimizing the environmental, and process safety objective, and maximizing economic objective, the natural gas sweetening process is a perfect contender for multi-objective optimization. Several multi-objective optimization cases are studied and solved in MS Excel-visual basic application interfaced with natural gas sweetening process simulator (i.e., Aspen-Hysys). The acidification potential for environmental objective, damage index for process safety, and profit before tax is successfully optimized together with the enhanced removal of acid gas for the industrial natural gas sweetening process. Pareto-optimal solutions are obtained for all multi-objective optimization problems studied. The temperature and pressure of the feed gas, the flow rate of the feed gas, and the temperature of the regenerator are the most influencing operating variables among the seven decision variables used in this study. Energy-saving potential and profitability analysis of the operating plant has also been established under normal and deteriorating feed conditions to meet the desired sweet gas purity and process safety, which has resulted in improvement of damage index (DI), profit before tax (PBT) and energy savings under normal feed quality approximately by 2%, 16% and 4.5 × 105 kJ/h, respectively. An identical H2S removal (i.e., 98.8%) with ~9% energy conservation can be achieved in the same plant for deteriorating feed quality by compromising ~ 6% DI and ~6.5% PBT.
AB - In this study, multi-objective optimization of the methyl di-ethanolamine-based industrial natural gas sweetening process is carried out using the improved multi-objective differential evolutionary algorithm for the enhancement of the plant performance by tuning the critical process parameters. Due to the involvement of conflicting objectives, i.e., minimizing the environmental, and process safety objective, and maximizing economic objective, the natural gas sweetening process is a perfect contender for multi-objective optimization. Several multi-objective optimization cases are studied and solved in MS Excel-visual basic application interfaced with natural gas sweetening process simulator (i.e., Aspen-Hysys). The acidification potential for environmental objective, damage index for process safety, and profit before tax is successfully optimized together with the enhanced removal of acid gas for the industrial natural gas sweetening process. Pareto-optimal solutions are obtained for all multi-objective optimization problems studied. The temperature and pressure of the feed gas, the flow rate of the feed gas, and the temperature of the regenerator are the most influencing operating variables among the seven decision variables used in this study. Energy-saving potential and profitability analysis of the operating plant has also been established under normal and deteriorating feed conditions to meet the desired sweet gas purity and process safety, which has resulted in improvement of damage index (DI), profit before tax (PBT) and energy savings under normal feed quality approximately by 2%, 16% and 4.5 × 105 kJ/h, respectively. An identical H2S removal (i.e., 98.8%) with ~9% energy conservation can be achieved in the same plant for deteriorating feed quality by compromising ~ 6% DI and ~6.5% PBT.
KW - Deteriorating feed
KW - Energy-saving
KW - Multi-objective differential evolutionary algorithm
KW - Natural gas processing
KW - Optimization
KW - Pareto ranking
KW - Process safety
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U2 - 10.1016/j.jngse.2021.104207
DO - 10.1016/j.jngse.2021.104207
M3 - Article
AN - SCOPUS:85113283471
SN - 1875-5100
VL - 95
JO - Journal of Natural Gas Science and Engineering
JF - Journal of Natural Gas Science and Engineering
M1 - 104207
ER -