To ensure compliance with dew point requirements and achieve low energy consumption in the natural gas dehydration process, this study utilizes Aspen HYSYS to simulate the natural gas dehydration process, using a gas field gathering station as an illustrative example. Through an in-depth analysis of operational parameters, we have successfully identified the optimal variables that significantly impact the energy consumption of the dehydration system. The Box-Behnken design (BBD) experimental design approach is employed, and parameter optimization is performed using the non-dominated sorting genetic algorithm (NSGA-II). Our findings indicate that variations in Tri ethylene glycol (TEG) circulation rate, reboiler temperature, and steam stripping rate are highly sensitive to energy consumption. Analysis of the Pareto front reveals that under similar dew point conditions before and after optimization, there is a notable reduction in specific energy consumption by 4.18% compared to the pre-optimization state. Conversely, when specific energy consumption is comparable, optimization results show a decrease in dry gas dew point by 1.92°C after optimization. Furthermore, comparison with optimization results obtained using HYSYS's built-in optimizer demonstrates reductions in both TEG circulation rate and steam stripping rate. In summary, the NSGA-II algorithm demonstrates superiority in reducing energy consumption and optimizing parameters by providing globally optimal solutions. This research presents an efficient solution for optimizing energy consumption in natural gas dehydration while enhancing process efficiency and economic benefits.

Nihad AL-MADHKHOORI, Huimin Liu. Energy analysis and parameter optimization of TEG dehydration utilizing the NSGA-II algorithm. Academic Journal of Computing & Information Science (2024), Vol. 7, Issue 10: 147-156. https://doi.org/10.25236/AJCIS.2024.071020.

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