Thermodynamic analysis and multi-objective optimization of a novel power system with advanced adiabatic compressed air energy storage

The increasing need for energy increases the interest in energy storage systems and renewable energy sources. The fluctuations, which are the disadvantage of renewable energy sources, are desired to be eliminated with energy storage systems. In this regard, compressed air energy storage system which allow the mechanical storage of large amounts of energy have attracted a lot of attention among energy storage systems in recent years with their advantages. However, these systems need to be developed in order to be feasible and sustainable. In order to improve the operating performance of these systems, it is important to identify and optimize the source of exergy destruction of the system components and their interrelationships. In this study, an advanced adiabatic compressed air energy storage system with a power output of 10 MW is proposed. Conventional/advanced exergy and exergy-economic analyses of the proposed system are performed and the interrelationships among the components are investigated. In addition, parametric analysis and multi-objective optimization of the proposed system are carried out. In the multi-objective optimization study, the Non-dominated Sorting Genetic Algorithm-II method is used and the objective functions are determined in conventional and advanced exergy/exergy-economic analysis concepts. A new performance criterion for advanced exergo-economic analysis that is not available in the literature is determined and the results are validated with conventional exergo-economic analysis.