IEA-SHC INFO SHEET 45.B.3.1 - Seasonal Borehole Thermal Energy Storage – Guidelines for Design & Construction
Bibliographic record
Abstract
Borehole thermal energy storage (BTES), which is also referred to as duct storage, has been successfully used for seasonal heat storage in a number of large solar systems.Some of these systems utilize a heat pump to upgrade the stored energy to the load temperature while others use the stored heat directly without upgrading.Borehole thermal energy storages have also been used for storing cold.BTES use the heat capacity in a large volume of native soil to store thermal energy underground.The soil itself is a very good medium for large heat storage systems since it is no-cost, already on-site, involves minimal excavation, is non-toxic and has a reasonable heat capacity.Much of the cost of a BTES is in the heat exchanger used to transfer heat to and from the soil, the drilling of boreholes in which to install the heat exchanger and in the insulation which is placed over the top of the store.For smaller storages (up to 5 000 m 3 ) typically an insulated steel tank is used but for large storages a BTES can be considerably cheaper per unit volume of water-equivalent storage.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.161 | 0.113 |
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".