Performance and economic assessment of an advanced adiabatic compressed air energy storage system integrated with a low-cost expansion device

Advanced Adiabatic Compressed Air Energy Storage (AA-CAES) is promising for large-scale storage, but the capital cost of conventional turbomachinery hinders distributed deployment. We propose an AA-CAES system integrating a low-cost bladeless Tesla turbine and a unified techno-economic framework. The framework couples thermodynamic calculations, a condition-dependent feedforward neural network turbine surrogate, and hybrid component cost models. Two-stage particle swarm optimization first screens candidate topologies and then updates turbine efficiency at each operating point. The converged design is evaluated against a conventional-turbine baseline. This coupling links condition-dependent component performance to the scale-dependent economic assessment. The optimized design raises RTE from 27.6% for direct turbine substitution to 39.3% and reduces initial investment by about 49%. At full scale, its levelized cost of storage (LCOS) is 0.208 USD/kWh versus 0.184 USD/kWh for the conventional baseline. Under the modeled costs, duty cycle, financing, and scaling assumptions, the LCOS curves cross near 4500 kW; below this case-specific boundary, the Tesla-turbine system has lower modeled CAPEX and LCOS. These results define a bounded distributed-storage niche rather than a universal commercial threshold.