A Systematic Review of Numerical Modelling Approaches for Cryogenic Energy Storage Systems

Cryogenic Energy Storage (CES) has emerged as a promising solution for large-scale and long-duration energy storage, offering high energy density, zero local emissions, and compatibility with intermittent renewable energy sources. This systematic review critically examines recent advances in the numerical modeling of CES systems, with the objective of identifying prevailing methodologies, emerging trends, and existing research gaps. The studies analyzed are classified into three main categories: global thermodynamic modeling, simulation of specific components, and transient dynamic modeling. The findings highlight the continued use of thermodynamic models due to their simplicity and computational efficiency, alongside a growing reliance on high-fidelity CFD and transient models for more realistic operational analyses. A clear trend is also observed toward hybrid approaches, which integrate deterministic modeling with machine learning techniques and response surface methodologies to enhance predictive accuracy and computational performance. Nevertheless, significant challenges persist, including the absence of multiscale integrative models, the scarcity of high-resolution experimental data under transient conditions, and the limited consideration of operational uncertainties and material degradation. It is concluded that the development of integrated numerical frameworks will be critical to advancing the technological maturity of CES systems and ensuring their robust deployment in real-world energy transition scenarios. Additionally, the review also discusses local thermal non-equilibrium (LTNE) conditions, the influence of geometric and operational parameters, and the role of multidimensional and multi-region modeling in predicting thermal and exergy performance of packed-bed TES within LAES cycles.