Parametric assessment, multi-objective optimization and advanced exergy analysis of a combined thermal-compressed air energy storage with an ejector-assisted Kalina cycle

Compressed air energy storage has attracted worldwide attention owning to its low capital investment, scalability, eco-friendliness and long life. In this paper, a new combined thermal-compressed air energy storage with ejector-assisted superheated Kalina cycle is comprehensively investigated. Parametric assessment at the aspect of thermodynamic and economic performances is first conducted to investigate the influence of several crucial design parameters. Multi-objective optimization is then carried out based on genetic algorithm to maximize the round-trip efficiency and economic profits. Finally, the advanced exergy analysis is performed to achieve more valuable information by taking the component interconnections and technological limitations. Results demonstrate that increasing charging pressure, separation temperature, and ammonia mass fraction of basic solution and decreasing compressor effi-ciency are beneficial to reduce the investment cost per product. Meanwhile, the investment cost per product exists an optimum value along with the pinch temperatures of cooler and heater, discharging pressure and turbine efficiency. The system round-trip efficiency and investment cost per product are respectively 52.92% and 0.087 $/kWh based on multi-objective optimization. The advanced exergy analysis results indicate that interactions among components are weak and the system has a large potential for improvement due to higher avoidable exergy destruction than unavoidable part. (c) 2021 Elsevier Ltd. All rights reserved.

Automated summary

Increasing certain key parameters such as charging pressure, separation temperature, and ammonia mass fraction in the basic solution, while decreasing compressor efficiency, can help reduce the investment cost per product. Additionally, optimizing the design can improve system round-trip efficiency and economic profits.