Employing static and dynamic optimization approaches on a desiccant-enhanced indirect evaporative cooling system

Abstract

The best possible condition for employing desiccant-enhanced indirect evaporative cooling system (DEVap) as efficient as possible in four cities of Iran is found. To achieve this purpose, both static and dynamic optimization approaches are employed for design as well as retrofit stages, using the combination of non-dominated sorting genetic algorithm II (NSGA-II) and TOPSIS method as the ordering technique by similarity to ideal solution. As a result, four optimization scenarios are defined. Through a comprehensive comparative study among the optimum results, the best optimization strategy for each city is suggested. Both dimensional characteristics and operational parameters of the cooler are considered as decision variables while necessary technical and geometrical constraints such as thermal comfort condition are imposed. In addition, life-cycle cost (LCC), annual average coefficient of performance (ACOP), annual water consumption (AWC), and annual carbon dioxide emission (ACE) are optimized as the objective functions. It is found that for all the four investigated cities and both design and retrofit stages, dynamic optimization approach offers better results. Compared to the base condition, which is the static retrofit optimization, dynamic retrofit optimization results in 23.7, 50.5, 153.2, and 57.8% improvement in LCC, ACOP, AWC, and ACE, respectively. The average enhancement of the four mentioned objective functions for dynamic design optimization are 34.6, 60.1, 390.0, and 69.9%, respectively.