Abstract
This work deals with the optimization of an existing industrial cryogenic air separation plant with respect to exergy efficiency and argon recovery. A previously validated simulation model of the plant was used, and the operating conditions and specifications of the process correspond to those reported in the historical records of an air separation facility in Colombia. The optimization is carried out considering the variation in the historical demand and the installed capacity of the plant, using an elitist nondominated sorting genetic algorithm (NSGA-II). As exergy efficiency and argon production goals are in conflict, a Pareto front of optimal solutions is obtained for the assessed variables. It is found that under optimal conditions of the pareto fronts, exergy efficiency and argon recovery can be enhanced up to 30 % and 23 %, respectively, with respect to recommended operating conditions from the plant manual. Also, obtained results indicate that the plant operated with larger air feed flowrates than required for the corresponding specific monthly demands. Under the optimal conditions, the plant could operate with a 58 % average reduction in the specific energy consumption (0.53 kW/Nm3O2) and larger argon recoveries. This represents a major improvement in the profitability of the operation and its sustainability indicators.
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