Abstract
In this paper, an exergy analysis approach is proposed for optimal design of distillation column by using simulated annealing algorithm. First, the simulation of a distillation column was performed by using the shortcut results and irreversibility in each tray was obtained. The area beneath the exergy loss profile was used as Irreversibility Index in the whole column. Then, First Optimization Algorithm (simulated annealing, SA) was implemented to Grassroots (Number of tray (N) vs. Reflux Ratio (RR)) and Retrofit (Nof vs. Feed splitting) cases, respectively. Next, SA was used to find the maximum recovery in a simple column by seven different variables (Feed Temperature, Feed Pressure, Reflux Rate, Number of theoretical stage, Feed Trays (Feed Splitting, three variables)) simultaneously. During the search for maximum recovery, it was tried to find a better Irreversibility Index. In the second part, SA optimization algorithm was used for a complex column with one pump-around and feed splitter to find a better condition, which means to find the best location for pump-around and feed trays in Distillation column. The main objective in SA was to maximize the recovery of the desired component and to find a better minimum Irreversibility Index. This method was implemented in de-ethanizer; in the first optimization without using pump-around with seven degrees of freedom, Recovery growth was 5.1% and reduction in irreversibility index was 3%. At the best Irreversibility Index, growth of recovery was about 3.7% and irreversibility index reduction was 25%. In the second optimization with pump-around or eight different variables, in the best condition, Recovery Growth was 6.2% but had a very high Irreversibility Index. At the best irreversibility index, recovery reduction was 17% but reduction in irreversibility index was about 21% comparing with initial point. As a result, it is shown that, regarding recovery and Irreversibility, pump-around shouldnt be used in a column. Without using pump- around, a better condition, considering both factors, can be achieved.
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