Optimization of a fin-and-tube latent thermal energy storage for domestic hot water application

Latent thermal energy storage systems offer a compact solution for domestic hot water applications. However, their adoption is limited by the high heat exchanger cost, mainly due to the copper and aluminium required to compensate for the low thermal conductivity of the phase change material. Reducing the material used while maintaining performance remains a critical challenge. This study presents a novel optimization framework based on a fast numerical model of a fin-and-tube latent thermal energy storage coupled with a genetic algorithm. The framework identifies improved configurations for domestic hot water production by evaluating each geometry through indicators related to practical use, namely the delivered water volume at 40 °C, the occupied volume and the heat exchanger cost. A two-dimensional axisymmetric model with separate charging and discharging circuits is developed, including fin geometry and the supercooling behaviour of the material. The model is validated under representative operating conditions, yielding root mean square deviations of the outlet water temperature below 0.5 °C during charging and 2 °C during discharging. Neglecting supercooling led to an overestimation of the heat transfer rate by up to 30%, showing its importance for accurate discharge prediction. The optimization assessed 580 configurations over complete charge and discharge cycles. The selected configuration reduced the heat exchanger cost by 22.2% and improved the performance-to-cost ratio by 7.6% relative to a reference commercial design. The proposed optimization framework could support storage design for domestic hot water applications.