Exergy, economy and pressure drop analyses for optimal design of recuperator used in microturbine

The optimal design of a plate-fin recuperator of a 200-kW microturbine was studied in this paper. The exergy efficiency, pressure drop and total cost were selected as the three important objective functions of the recuperator. Genetic Algorithm (GA) and Non-dominated Sorting Genetic Algorithm (NSGA-II) were respectively employed for single-objective and multi-objective optimizations. By optimizing the objective functions via the single-objective optimization approach, the optimum values of exergy efficiency, pressure drop and total cost were found to be 0.966, 0.846 kPa, and 302,075$ respectively, representing the best solutions obtained from 20 iterations in GA. The cases considered for bi-objective optimizations were exergy efficiency-total cost, exergy efficiency-pressure drop and total cost-pressure drop pairs for which Pareto-optimal fronts were obtained, revealing the confliction between the two objectives in each pair. Later, a three-objective optimization was undertaken to simultaneously maximize exergy efficiency while minimizing pressure drop and total cost; the results were presented in a three-dimensional Pareto-optimal front. Moreover, the results of the multi-objective optimizations (i.e. three-objective and bi-objective optimizations) were compared with those of the single-objective one. The comparisons indicated a very good match between the multi-objective and the single-objective optimum values when it came to exergy efficiency and total cost; for pressure drop, however, significant differences were observed. Eventually, a decision-making procedure was employed for the Pareto-fronts of multi-objective optimization to find the final optimal solution.