Performance optimization of an industrial natural gas dehydration process to reduce energy consumption and greenhouse gases (GHGs) emission

Natural gas dehydration using multi-layer adsorption beds is one of the most essential processes in gas processing plants, where the water molecule is removed from raw gas by a continues cyclic temperature swing adsorption operation. In the present research, a commercial adsorption unit for dehydration of natural gas has been studied, and the effects of the volume of adsorbents in the multi-layer adsorption beds on the overall performance of the process have been investigated using a precise mathematical model. The numerical method of lines (NMOL) has been applied to solve the partial differential equations (PDEs) demonstrating the fixed bed. The real plant data from the industrial unit have been used for validation of the model. The simulated breakthrough time, bed pressure drop, and dried gas temperature are found to be in good agreement with experimental measurements with an error of less than 4%. The modelling results are applied to obtain the optimum adsorbents layers' configuration using response surface methodology (RSM). The objective functions are pressure drop and water breakthrough time, while variables are the length of two molecular sieve layers with different particle sizes, which are loaded in each adsorption column. The results indicated that an 18.45% reduction in the direct and indirect greenhouse gases (GHGs) emission (35 369.59 MT/year) during the regeneration cycle and a significant decrease in energy consumption (623 609 GJ/year) can be achieved by applying the optimal configuration. Moreover, 1 year longer continuous operation (by avoiding nearly 45 regenerations) is another desirable outcome of the optimization.