Predictive approach of heat transfer for the modelling of large-scale latent heat storages

Thermal energy storage systems based on phase change materials are interesting candidates to handle the difficulties raised by intermittent renewable sources or by batch processes. Among these systems, many rely on the use of steam, as for instance in concentrating solar power plants or district heating, or in the pharmaceutical or food industries. Today, there is no systematic method to design such systems quickly and easily since complex heat transfer is observed due to the influence of the geometry and to the dual characteristics associated with solid/liquid and liquid/gas transitions. The aim of the present work is thus to propose a multi-scale modelling methodology of a latent heat storage system for the storage of steam. It mainly involves two different simulation models with different scales for the heat transfer fluid and the phase change material. Furthermore, it relies on the use of a heat transfer correlation based on specific non-dimensional numbers, which is deduced from previous simulations of the phase change material’s behavior, obtained with fine 3D computational fluid dynamics calculations. Consequently, a reduced model is built to simulate the whole system. This model does not need to be tuned against experiments. This model is then directly used to compare the numerical results with measurements coming from a prototype scale latent heat storage available at CEA Grenoble. The results are very promising and show that an a priori approach that is more physically consistent and not based on any model tuning can lead to acceptable results. Moreover, the computational time can be divided by 10–40, thus allowing future design and real performance evaluations of latent heat storage modules.