Thermal energy storage (TES) systems have been extensively employed as an elegant approach to partially fulfill the enormous energy demand in industrial applications, such as mining, geothermal, oil and gas, and construction industries by deploying the available renewable energies or using alternative energy solutions. TES allows for energy to be stored in the form of heat during times of low/no demand and used later when demand rises. Energy storage efficiency depends on many design and operational factors, which are not easy to empirically quantify. Among these factors, the permeability of porous media is not well-understood and plays a fundamental role on storage efficiency. Computational modelling is a feasible approach to predict the primary parameters to design and evaluate and optimize the performance of TES systems. Hence, this study begins with a comprehensive review of fluid flow and heat transfer mechanisms in porous media. Then, numerical investigation was performed to estimate the pressure drop through the packed bed of large spherical particles with two sets of models: pore-scale and volume-averaged. The numerical models were developed, analyzed, and validated with experimental data. Further, a new Ergun/Forchheimer correlation was proposed and employed to study the impact of various design and operating parameters, such as porosity, particle size, mass flowrate, aspect ratio, properties of storage material, and inlet air temperature on the overall performance of large-scale TES systems. Two energy sources were used based on their availability in the field: seasonal ambient air and exhaust streams from a diesel generator. The fluid flow behavior inside a packed rock bed thermal energy storage system was investigated by developing a transient, 3D computational fluid dynamics and a heat transfer model that accounts for interphase energy balance for energy conservation, using a local thermal non-equilibrium approach. The heat transfer phenomenon in the rock-pile was empirically validated. The model also provides useful information for evaluating the performance of packed beds of large rocks and in caved zones. The proposed TES system has great potential to be a green solution to meet heating/cooling and ventilation demands of deep underground mines, as well as the heating demand of the remote communities in the cold climates by reducing the burning of fossil fuels and carbon emissions.