Dynamic heat transfer model for thermal energy storage using metal wool–phase change material composites

Abstract

Decarbonisation of the energy sector is critical for climate change mitigation, with the power sector remaining a major contributor to global emissions. Concentrating solar power (CSP) technology combined with thermal energy storage (TES) presents a promising solution to overcome this challenge. TES systems, particularly those utilising phase change materials (PCMs), offer efficient energy storage by harnessing latent heat, enabling reliable power generation, and providing high-temperature heat for industrial processes. This research introduces a heat transfer model designed to simulate the thermal behaviour of TES systems utilising wool–PCM composites as storage medium. The mathematical model was implemented on the OpenModelica platform and it is intended to be incorporated into a simulation tool currently being developed by the authors to assess the performance of CSP plants under dynamic conditions. The model was validated by comparing the simulation results with the experimental measurements of the temperature within the composite domain during both the charging and discharging cycles. The simulations replicated key experimental parameters, including geometry, material properties, and boundary conditions, and evaluated two configurations with coarse and fine wool fibres. The results demonstrated good agreement with the experimental data for coarse wool, with a root mean square error (RMSE) of up to 2.29 K. For fine fibres, the RMSE increased to 5.31 K, indicating a larger deviation. Despite these challenges, the model successfully captured the overall thermal response trend and phase transition behaviour observed experimentally. The findings highlight the efficacy and limitations of the proposed thermal model and emphasise the necessity for advanced macroscopic-scale effective thermal conductivity modelling approaches for such composites that integrate the influence of pore-scale characteristics (i.e., volume change). This research will advance the current state-of-the-art in this field and will mitigate the discrepancies identified in this study when these models are applied in practice. This integration is crucial for enhancing the accuracy and improving the time simulation of large-scale TES systems in CSP applications.