In view of the high energy consumption in dry gas concentration unit,the latest middle-cool oil flash process is studied.Aspen Plus software is utilized for process simulation,and an improved genetic algorithm(NSGA-Ⅱ)is used.Taking the annual total cost(TAC),CO2 emissions(Ecarbon)and C2 recovery(RC2)as the objective functions,the penalty function method is used to transform the problem into an unconstrained problem.A multi-objective optimization is conducted on the middle-cool oil flash process to obtain a Pareto front.After statistics,it is found that the coefficient of variation for the mass ratio of semi lean liquid to lean liquid is only 2.37%,which can be represented by an average value of 1.95.Finally,the TOPSIS method is employed to select the best solution.The optimization results show that compared with the shallow-cool oil absorption process,the RC2 of the middle-cool oil flash process increases by 3.09%,the TAC decreases by 43.75%,and the Ecarbon decreases by 41.77%.It is shown that the performance of middle-cool oil flash process shows a great improvement in all properties,and the multi-objective optimization method based on NSGA-Ⅱalgorithm can help to find more beneficial conclusions.
dry gas concentrationgenetic algorithmmulti-objective optimizationprocess simulationoptimal designabsorption
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