Abstract

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.

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