This study introduces a new analytical framework that employs the image‐well method to simulate the spatial and temporal temperature distribution in vertical borehole thermal energy storage (BTES) systems. The model accommodates complex boundary shapes and conditions, including insulation, convection, and constant temperature, without requiring iterative solutions at each time step. The model's accuracy and utility are demonstrated through an application to a borehole heat exchanger cluster arranged in an octagonal shape with insulating boundaries, based on a BTES site in Drake Landing (Canada). Model predictions are validated against a finite element model, showing a root‐mean‐square error of 0.012°C. A global sensitivity analysis highlights the influence of thermal parameters on system performance, identifying the heat flux of the borehole heat exchanger as the most sensitive parameter. Overall, this approach combines the advantages of analytical and numerical techniques to provide a clear and efficient tool for evaluating BTES systems, offering significant potential for advancing sustainable energy solutions.
This study introduces a new analytical framework that employs the image‐well method to simulate the spatial and temporal temperature distribution in vertical borehole thermal energy storage (BTES) systems. The model accommodates complex boundary shapes and conditions, including insulation, convection, and constant temperature, without requiring iterative solutions at each time step. The model's accuracy and utility are demonstrated through an application to a borehole heat exchanger cluster arranged in an octagonal shape with insulating boundaries, based on a BTES site in Drake Landing (Canada). Model predictions are validated against a finite element model, showing a root‐mean‐square error of 0.012°C. A global sensitivity analysis highlights the influence of thermal parameters on system performance, identifying the heat flux of the borehole heat exchanger as the most sensitive parameter. Overall, this approach combines the advantages of analytical and numerical techniques to provide a clear and efficient tool for evaluating BTES systems, offering significant potential for advancing sustainable energy solutions.
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