Solar Thermal Trigeneration System in a Canadian Climate Multi-unit Residential Building
Bibliographic record
Abstract
This paper presents the comparison of several solar thermal, cogeneration and thermally driven heating/cooling central plant systems implemented into a typical mid-rise apartment, located in Calgary, Alberta, Canada. TRNSYS is used to model the system and predict the primary and secondary energy consumption, greenhouse gas (GHG) emissions and annual utility costs of the various systems and compared to the base case. The highest annual utility cost and GHG emission savings was attained by operating a cogeneration device in priority in a solar thermal, cogeneration with absorption heat pump plant, predicting a 21% reduction in the annual utility cost and a 16% reduction in GHG emissions. The system however has a higher secondary energy consumption, 10% above the base case. Operating the solar thermal collectors in priority over the cogeneration unit in the same central plant the greatest primary and secondary energy savings were attained achieving 16% and 18% savings compared to the base case. GHG emission savings of 16% was predicted with both operating strategies. Comparing this system to a cogeneration only system, secondary energy savings of 36% are predicted demonstrating the benefit of adding solar thermal collectors and a thermally driven heat pump to a cogeneration system. Extending the operating period of the solar thermal and cogeneration system by adding a thermally driven chiller did not yield significant primary energy, secondary energy, GHG emission or utility cost savings over a heating only system. This is attributed to extended operating period of the single stage boiler with poor part load performance. Finally, due to the low natural gas utility costs and higher electricity rates, the systems operating the cogeneration system in priority always resulted in the highest utility cost savings and the addition of solar thermal and thermally driven heating/cooling had limited economic benefit.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".