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December 4, 2025Case Studies in Thermal Engineering0 citationsOpen Access

Techno-economic analysis and multi-objective optimization of an adiabatic compressed air energy storage system integrated with cascaded molten salt thermal energy storage

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FYFan YangSino Biopharmaceutical (China)YCYue CaoNanjing Agricultural UniversityTHTianyu HeCentral South University

Key Points

  • Optimization enhances system performance through multi-objective analysis, improving efficiency and cost metrics.
  • The expansion ratio distribution impacts the system's performance in energy storage applications significantly.
  • This analysis integrates advanced thermal energy storage and adiabatic compressed air systems for more effective energy grid management.
  • Findings suggest that improvements in storage efficiency may advance the use of renewable energy sources effectively.

Abstract

The integration of renewable energy sources poses challenges to the stability of the power grid. Compressed air energy storage (CAES) is one of the effective technologies for smoothing grid fluctuations, as it can store energy during low-power periods and release it when needed. This study proposes a large-scale high-temperature adiabatic CAES (HTA-CAES) system integrated with a cascaded molten salt heat recovery thermal energy storage (TES) system, and analyzes the thermodynamic and techno-economic performance of the proposed system. The feasibility of the system and its superiority over traditional systems were evaluated through thermo-economic analysis, and the effects of design conditions such as compression ratio distribution and expansion ratio distribution on system performance were investigated. A multi-objective optimization was performed using the non-dominated sorting genetic algorithm III (NSGA-III) to obtain the optimal solution balancing system round-trip efficiency (RTE) and levelized cost of energy (LCOE). Results show that the HTA-CAES system exhibits better performance than traditional systems, with an RTE of 71. 56 % under design conditions. The multi-objective optimization considering both RTE and LCOE highlights significant improvements in system performance: RTE, LCOE, energy storage density, and dynamic payback period are enhanced to 72. 21 %, 6. 79 × 10−2 /kWh, 4. 97 kWh/m3, and 7. 55 years, respectively.

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Cite This Study

Yang et al. (2025) studied this question.

synapsesocial.com/papers/694023c82d562116f28fcccchttps://doi.org/10.1016/j.csite.2025.107486
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