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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