Techno-economic evaluation is vital for assessing long-duration energy storage. Here, we present a computational workflow evaluating adiabatic compressed air energy storage economic performance. We describe steps for deriving learning-driven cost projections via experience-curve modeling and quantifying uncertainties using Monte Carlo simulations. We then detail procedures for discounted cash flow analysis to determine costs. This protocol enables systematic assessment of storage economic viability. For complete details on the use and execution of this protocol, please refer to Yang et al.¹.