Experimental Analysis and Numerical Optimization of the Stratification Efficiency in a Commercial Stratified Thermal Storage

The ever-increasing demand for renewables in the energy system has drawn attention to technologies capable of minimizing the effect of renewables’ intermittency and shave-off the generation-demand imbalance of the system. Energy storage can help to level peaks in energy demand, thus reducing wastage due to excess capacity during off-peak demand periods. Among the storage media, thermal energy storages (TES) have a large variety of applications, ranging from solar energy utilization and power peaking to industrial waste heat storage. In this study, data collected from an operating commercial stratified tank are used to validate a 2-D axisymmetric CFD model. Temperature profiles at various heights are collected throughout one month with a one-minute refresh rate. The model replicating the tank is generated in COMSOL Multiphysics® and validated by emulating the registered charging phases of the real storage, thus comparing the temperature layers before and after the charging occurs. The model is then employed to optimize the stratification efficiency of the tank, by varying the logics applied to pinpoint optimal values of both inlet water temperature and velocity. The study aims to minimize the MIX number, parameter often utilized in literature to identify the ability of the storage to generate and preserve optimal temperature stratification. Said dimensionless number is evaluated by accounting for the momentum of energy of the different temperature layers found in the water tank. Therefore, a discretization of the thermal storage in five sub-volumes, each of them characterized by the presence of an installed thermocouple, was defined. Finally, the experimental MIX number has been evaluated for the aforementioned temperature profiles.