Common approaches in designing natural gas dryers are based on empirical algebraic correlations and design heuristics. Such approaches fail to capture the process physics and are generally not optimal. In this work a new method for the design of natural gas dryers is presented. The method formulates a mixed integer nonlinear programming (MINLP) problem where the objective is to minimize the net present value of ensued costs (NPVC) of the drying system throughout its lifetime, while meeting all process constraints. Two process schemes based on common industrial conditions are considered, which differ in the source of the regeneration gas. Both schemes are shown to attain an optimal NPVC in the range of 4.5 to 5.4 $/MMSCF. When compared to conventional methods, this represents a reduction in the range of 17- 37%. The cost savings are primarily achieved from the optimization of the adsorption time, regeneration time, and the regeneration gas flow rate, thus illustrating the advantages of the proposed optimal design.
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© 2016 American Chemical Society.