Abstract
In this study, parametric analysis and multi-objective optimization of the advanced adiabatic compressed air energy storage system (AA-CAES) were performed. Non-dominated Sorting Genetic Algorithm (NSGA-II) method was used in the multi-objective optimization study. In the optimization study, objective functions were determined in the conventional and advanced exergy/exergo-economic analyses concept. In the optimization study in the concept of advanced exergo-economic analyses, a new performance criterion that is not in the literature was determined and the results were confirmed by conventional exergo-economic analyses. In this study, the modified total unit product cost, which is given as the new performance criterion, is defined on the basis of avoidable feed exergy cost rate and avoidable investment cost rate. This shows the potential to be improved in the cost of the system and gives more detailed information than the total unit product cost in conventional exergo-economic analysis. As a result of the optimization study, the total unit product cost and the exergy efficiency of the system were found to be 162.9 $/day and 64.3%, respectively for the conventional exergy/exergo-economic analyses concept. For the advanced exergy/exergo-economic analyses concept, the modified total unit product cost and the modified exergy efficiency of system were found to be 103.5 $/day and 91.9 %. The exergy efficiency and the total unit product cost improved by 16.48 % and 3.55 %, respectively, with the optimization study according to the basic case of the overall system. With the parametric study, the increase in the efficiency of the wind turbine affected the exergy destruction rate more than the other system components. While the effect of the increase in the efficiency of the turbines on the exergy destruction cost rate of the system is greater than the other system components, the system component that most affects the cost rate of the system is the compressors.
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