# Protocol for evaluating the economic viability of adiabatic compressed air energy storage systems

## TL;DR

This paper introduces a protocol to assess the economic viability of adiabatic compressed air energy storage systems using cost projections and financial models.

## Contribution

The novel contribution is a computational workflow combining experience-curve modeling and Monte Carlo simulations for techno-economic evaluation of CAES systems.

## Key findings

- A protocol is developed for learning-driven cost projections using Wright’s law modeling.
- Monte Carlo simulations quantify uncertainty in experience rates for CAES systems.
- Discounted cash flow analysis is detailed to evaluate financial viability over a lifecycle.

## Abstract

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

•Harmonize global CAES cost data across currencies and inflation years•Derive learning-driven cost projections using Wright’s law modeling•Quantify experience rate uncertainty via Monte Carlo simulations•Assess financial viability through a lifecycle DCF and PVR-TCO model

Harmonize global CAES cost data across currencies and inflation years

Derive learning-driven cost projections using Wright’s law modeling

Quantify experience rate uncertainty via Monte Carlo simulations

Assess financial viability through a lifecycle DCF and PVR-TCO model

Publisher’s note: Undertaking any experimental protocol requires adherence to local institutional guidelines for laboratory safety and ethics.

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.