Potential benefits of hybrid space heating with ASHP and natural gas furnace for a restaurant archetype
Bibliographic record
Abstract
This study evaluates the annual space heating energy costs, associated greenhouse gas (GHG) emissions, and overall system energy factors (EF) of a restaurant archetype in Toronto, Ontario, Canada utilizing hybrid space heating system consisting of electric cold climate air-source heat pumps (ccASHP) and natural gas furnaces (NGF). Different switching scenarios for the hybrid space heating, i.e., Smart Dual-Fuel Switching System (SDFSS) and fixed temperature switching methods, were considered for this study and the results were compared against traditional NGF-only space heating method. For the ccASHP configurations of 4 to 6 units combined and NGF efficiencies of 80%, 85%, and 90%, the SDFSS governed hybrid heating systems were found to be consistently more effective than various fixed-temperature switching and NGF-only heating in terms of energy cost reduction. The SDFSS hybrid space heating resulted in an annual cost reduction ranging from 3.37% to 12.91% for the current carbon price (CP) rate of $65/tonne of CO₂. Moreover, the SDFSS contributed to a significant reduction in annual GHG emissions, ranging from 25.30% to 72.78% compared to NGF-only heating under the current carbon price settings. The study includes a sensitivity analysis, crucial in the context of evolving environmental policies. As carbon price rates increase from $65 to $170 per tonne of CO₂ by 2030 in Canada, the SDFSS hybrid space heating system yields higher reductions in terms of costs and GHG emissions compared to NGF-only heating. This analysis underscores the SDFSS governed hybrid system’s robustness in adapting to changes in economics and environmental aspects of space heating.
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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".