0D physical model for the charging phase of shell-and-tube Latent Heat Thermal Storage

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Abstract The transition to sustainable energy raises many issues that need to be addressed in order to develop reliable energy production infrastructures. Among these challenges, the mismatch between primary energy sources and energy loads stands out as a significant barrier to the widespread adoption of renewable technologies. Efficient energy storage solutions are crucial to mitigate this mismatch and facilitate the integration of renewable energy sources into existing grids. In this study, to evaluate the performance of this component within any plant, we focus on developing a simple yet effective model for predicting the behavior of shell-and-tube latent heat thermal energy storage (LHTES) systems limiting the analysis to the melting phase. LHTES systems offer promising potential due to their high energy density and ability to store thermal energy at a slightly constant temperature. However, their performance depends on various factors such as material properties, geometry and operating conditions, which require accurate predictive models for optimization and design purposes. Our proposed model uses fundamental principles of heat transfer and phase change phenomena to simulate the behavior of LHTES systems during the melting phase. By considering factors such as heat transfer coefficients, phase change kinetics and thermal properties of the storage medium, our model aims to provide insight into the thermal performance and efficiency of shell-and-tube LHTES configurations. Through validation against experimental data and numerical simulations, we demonstrate the effectiveness of our model in accurately predicting key performance metrics such as charge rates, temperature distribution within the storage medium, and overall energy storage efficiency. Its simplicity and computational efficiency make it suitable for practical applications, enabling engineers and designers to optimize LHTES systems for specific operating conditions and integration scenarios.