Empirical Validation and Numerical Predictions of an Industrial Borehole Thermal Energy Storage System
Abstract
:1. Introduction
2. Description of the Site and the Modelled BTES
3. Numerical Procedure
3.1. Numerical Model
- One-dimensional heat transfer between downward and upward flow
- One-dimensional heat transfer between grout (backfill material), liquid and ground
- Two-dimensional heat transfer around the borehole and between the grout and the liquid, using a mesh of cylindrical coordinates
3.2. The Modelled System and Validation Setup
3.3. Parametric Study
4. Results and Discussion
4.1. Model Validation and Time-Step Dependency
4.2. Parametric Study
4.2.1. Borehole Spacing
4.2.2. Borehole Depth
4.2.3. Ground Thermal Conductivity
4.2.4. Useful Storage Temperature
5. Conclusions
- For the investigated storage supply flows at heat injection, 10–20 l/s and 40–80 °C, a high temperature in the supply flow was more important than a high flow rate in order to achieve high annual heat extractions
- For a BTES there is a borehole spacing and depth at which heat extraction is the highest, which are possible to determine with the use of a numerical model such as the one used in this study
- Annual heat extraction quickly reduced as the spacing was decreased from the spacing yielding the highest annual heat extraction, whereas the reduction in annual heat extraction was quite slow when the spacing was increased from this point.
- Annual extracted energy was barely affected by a change in the effective ground thermal conductivity. However, the impact of the effective ground thermal conductivity is likely to have been greater at a higher temperature difference between the storage supply flow and the minimum storage temperature considered useful.
- Annual energy that could be extracted from the storage increased almost linearly with a decrease in the minimum storage temperature considered useful when the latter was decreased from 40 to 30 °C.
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
References
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Case | Mass Flow of Actual (%) | Flow Temperature of Actual (%) | Mass Flow Rate (kg/s) | Flow Temperature (°C) |
---|---|---|---|---|
Case 1 | 75 | 200 | 10 | 80 |
Case 2 | 150 | 150 | 20 | 60 |
Case 3 | 100 | 150 | 13 | 60 |
Case 4 | 75 | 150 | 10 | 60 |
Case 5 | 150 | 100 | 20 | 40 |
Case 6 | 100 | 100 | 13 | 40 |
Parameter | Values | Case |
---|---|---|
Borehole spacing (m) | 1, 2, 3, 4, 5, 6, 7, 8 | 1–6 |
Borehole depth (m) | 84, 114, 144, 174, 204, 234, 264, 294, 324 | 1–6 |
Modelled ground thermal conductivity (W/(m·°C)) | 1, 2, 3, 4, 5, 6, 7, 8 | 6 |
Minimum useful storage temperature (°C) | 30, 35, 40, 45 | 6 |
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Nilsson, E.; Rohdin, P. Empirical Validation and Numerical Predictions of an Industrial Borehole Thermal Energy Storage System. Energies 2019, 12, 2263. https://doi.org/10.3390/en12122263
Nilsson E, Rohdin P. Empirical Validation and Numerical Predictions of an Industrial Borehole Thermal Energy Storage System. Energies. 2019; 12(12):2263. https://doi.org/10.3390/en12122263
Chicago/Turabian StyleNilsson, Emil, and Patrik Rohdin. 2019. "Empirical Validation and Numerical Predictions of an Industrial Borehole Thermal Energy Storage System" Energies 12, no. 12: 2263. https://doi.org/10.3390/en12122263