The Influence of Energy Conservation on the Performance of Solar Thermal Systems – A Cold Country Case Study
Bibliographic record
Abstract
The European Union has set a goal that the energy use in the built environment shall be reduced by 41% to the year 2050 compared to 2005-2006. This could introduce new opportunities for solar thermal systems in cold countries. In such countries, like Sweden and Canada, the economy in solar thermal collector installation projects is often spoiled by the fact that most of heating energy demand of the building occurs during periods when the available solar energy is low. The present paper investigates the performance of solar thermal systems subjected to different quota between space heating and domestic hot water demand (DHW). This study investigates the performance of a solar thermal system integrated to four different buildings with varying heating loads in two different locations, Sweden and Canada. Models of single family houses are created which are able to simulate the total heating demand with different heating demand profiles but the same DHW demand. Simulations are performed in TRNSYS, an advanced tool used to simulate transient systems. Results indicate that solar combisystems tend to generate more useful energy and therefore be more cost effective when installed in buildings with higher heating demands.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".