Parametric Analysis of a Latent Heat Storage System for Predicting the Charging and Discharging Time

Abstract

Latent Heat Storages (LHS) are essential for harnessing renewable energy by storing surplus energy for later use. This research aims to enhance the predictability of charging and discharging times in LHS systems, a crucial step for effective energy management and optimizing renewable energy utilization. A comprehensive parametric analysis was conducted using computational fluid dynamics (CFD) to develop correlation equations for forecasting these times under diverse geometric and operational settings. Parameters considered includes the heat transfer fluid (HTF) inlet temperature, phase change material (PCM) thickness-to-length ratio, Reynold’s number, and HTF inlet location. The enthalpy-porosity method and Boussinesq model were employed in numerical simulations to account for natural convection during charging. The influence of the mushy-zone constant on the PCM’s temperature profile was investigated and found to be significant. The bottom HTF injection was found to reduce the charging times, while extending discharging durations. The thickness-to-length ratio of the PCM emerged as the most influential factor, with Reynold’s number exerting the least influence in the cycle. Analysis showed that increasing PCM thickness-to-length ratio consistently led to longer charging time. Four correlations were developed with an impressive average multiple R of 0.999463, signifying high predictability for charging and discharging times.