Abstract
A typical natural gas dehydration plant, which employs triethylene glycol (TEG) as the dehydrating agent, is simulated using a steady state flowsheeting simulator (Aspen Plus). All major units were included in the flowsheet, that is: absorption column, flash unit, heat exchangers, regenerator, stripper, and reboiler. The base case operating conditions are taken to resemble field data from one of the existing dehydration units operating in the United Arab Emirates (UAE). To explore effects of the thermodynamic model employed in the simulator on the reliability of the whole simulation process, different predictive mixing rules applied to two cubic equations of state (EOS), as programmed by the simulator, have been investigated. The EOS used in the simulation is the Redlich–Kwong–Soave (RKS) and the Peng–Robinson (PR), both with Boston–Mathias (BM) alpha function. In addition to the classical empirical mixing rules, the following ones are investigated: Predictive Soave–Redlich–Kwong–Gmehling (PRKS), Wong–Sandler (WS), and Modified-Huron–Vidal (MHV2) mixing rules. These mixing rules are all predictive in nature. The plant performance criteria that have been studied for their response to changes in the solvent circulation rate include: BTEX (benzene, toluene, ethyl benzene, and xylenes) emissions rate, desiccant losses (makeup), water content in the dehumidified natural gas, purity of the regenerated TEG, and reboiler heat duty. Comparison with the field data is done. Very diverse results have been obtained from the different models and mixing rules. No one single model gives the best results for all criteria.
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