Thermal energy storage system (TES) is a promising technology for buildings heating and cooling applications. Energy storage systems have been widely used for reducing energy use from peak-demand to off-peak times. Among the various thermal storage technologies, phase change materials (PCMs) are the most commonly used approaches for storing thermal energy for buildings heating and cooling application. These materials enable buildings to store and retrieve a considerable amount of energy, typically by being integrated into structural components through a wide variety of TES techniques. A centralized energy storage system can provide a part of the heating and cooling requirements of a low-energy building. Relatively little general information pertaining to the thermal characteristics of latent heat thermal energy storage (LHTES) systems are available; further investigation is required to analyze the thermal performance of centralized LHTES systems in buildings. In this dissertation, a 3-dimensional mathematical model of a centralized LHTES system is conducted and validated for both a quasi-steady state and a transient conjugate heat transfer problem. The model is then used to carry out a parametric study to investigate the effect of geometrical parameters, charging and discharging times and mass flow rates on the long-term system performance. 
Based on the parameters that could affect the long-term system performance, artificial neural networks (ANN) are developed not only to reduce the computational time but also to relate the outlet air-temperature to the inlet air-temperature of LHTES. The database obtained from the numerical solution is first used to train the ANN and then utilized to evaluate the accuracy of the trained ANN. The developed model is then integrated with a building’s mechanical ventilation system to investigate the potential improvement in occupants’ thermal comfort level and energy efficiency arising from the integration of the LHTES. It was found that the temperature difference between the air as a heat transfer fluid (HTF) and the PCM melting point has a significant effect on the performances of a LHTES system. The thermal energy retrieved from the centralized LHTES system is the highest when the inlet air temperature is about 10K higher than the PCM mean melting temperature.