Efficiency of a Community-Scale Borehole Thermal Energy Storage Technique for Solar Thermal Energy
Bibliographic record
Abstract
Solar thermal has been quite efficient in harvesting solar energy, but has not been used widely at the community-scale as thermal energy is difficult to store. Borehole thermal energy storage (BTES) has been recently researched by several countries for its suitability in storing excess heat generated from solar thermal panels during the summer times. The first community-scale BTES system in North America was installed in the town of Okotoke, Alberta, Canada in 2006 in order to supply partial winter heating energy for 52 residual houses. To better understand the working principles of BTES and to improve BTES performance for future applications at larger scales, a three-dimensional heat transfer model is established, using the 5- year in-situ monitoring data. The model realistically imposes the time-dependent heat injection and withdrawals rates measured at the site. A total of 10 continuous years of annual cycle are simulated. The modeling results are compared with the measured temperature data over the simulation times and space. The time-dependent temperature distributions within the borehole region agree well with the measured temperature profiles. The predicted energy recovery efficiency approaches to 27% after 10 years, which also compares well with the current year efficiency of 25% at the site.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".