(230a) Efficient Thermal Storage: Unveiling a 2D Computationally Efficient Borehole Thermal Energy Storage (BTES) Model for Renewable Energy Integration.

As we navigate towards an era dominated by the transition to entirely renewable energy sources, the search for viable, enduring energy storage methodologies becomes paramount. Within this evolving energy landscape, the technology of Borehole Thermal Energy Storage (BTES) emerges as a strategic asset for the smooth integration of renewable energies. However, the complex and resource-intensive nature of conventional 3D BTES modeling techniques poses significant barriers. This study introduces an innovative two-dimensional (2D) modeling technique designed to drastically reduce computational workload while maintaining good accuracy levels. Our approach rigorously models the intricate processes of thermal accumulation, retention, and release within a BTES framework across an extended seven-month timeline. A distinctive feature of our research is the deployment of the thermal mass average temperature parameter, an innovative concept that sheds new light on BTES system dynamics. The results of our investigation highlight the model's ability to improve BTES system efficiency, representing a substantial advance in the pursuit of enhancing renewable energy storage methods. Our findings reveal that this streamlined model operates with a speed that is seven times greater than conventional Computational Fluid Dynamics (CFD) models, showcasing an optimal balance of speed and accuracy. This investigation not only validates the practicality of this novel 2D approach but also sets the stage for future enhancements in BTES technologies, which are essential for propelling us towards a sustainable energy era. This endeavor seeks to spur ongoing innovation in the domain of energy storage solutions, further facilitating our global shift towards renewable energy adoption.