MARATTO

article · Next Energy

Thermal performance optimization of a macro-encapsulated PCM packed bed thermal energy storage system during charging and discharging processes: A validated CFD numerical study

2026Open accessAl Akhawayn University

Abstract

This study investigates the transient thermal performance of a latent packed bed heat storage system using spherical capsules of fully refined Paraffin Wax (PW60) during charging and discharging processes. A full-scale computational fluid dynamics model was developed using the Local Thermal Non-Equilibrium approach and the enthalpy-porosity method to capture the solid-liquid phase change dynamics within the phase change material. The model’s stability was verified through a rigorous mesh-independent study using 3 different meshes. The results were compared with the experimental data and showed good agreement with an average relative error of 3.22, assuring the validity and reliability of the present model. A multi-objective parametric study was conducted to study the effect of inlet temperatures and mass flow rates on thermal dynamics during the heat charging process. The results showed that increasing the temperature (Tin) from 75 to 90 °C accelerated the heat charging time by 37% and increased total heat stored E st and system efficiency by 18.18% and 13.65%, respectively. Similarly, increasing the inlet mass flow rate from 15 kg/h to 60 kg/h yielded a massive 68.78% reduction in charging time with an accumulated 9.7% efficiency drop. An optimal configuration of Tin = 85 °C and Qin = 30 kg/h was established, achieving a maximum storage capacity of 13 MJ. Finally, dynamic simulation of the full cycle of this optimized case showed a 25% acceleration in discharge compared to the charging phase. This confirms the system's powerful ability to recover energy quickly and efficiently in sustainable renewable thermal energy networks.

Research topics

  • Phase Change Materials Research
  • Adsorption and Cooling Systems
  • Solar Thermal and Photovoltaic Systems

Read the original research

This page summarises published work. The authoritative version sits with the publisher.

DOI: 10.1016/j.nxener.2026.100807

Is something wrong with this record? Report it or request removal.

Discussion

Discuss this research

Have you built on this work, tried to replicate it, or seen it applied in practice? Share what you know. Verified researchers and MARATTO™ domain experts can open a discussion, and any member can reply. Contributions are reviewed before they appear.

No discussion yet. Open the first thread.