Residential Air Source Heat Pump Water Heater Performance Testing and Feasibility Analysis in Cold Climate
Bibliographic record
Abstract
As new energy-efficient technologies emerge, space and water heating systems are continuously evolving. The latest generation of heating, ventilation, and air conditioning (HVAC) systems in Canada and other countries is shifting away from natural gas heating to cleaner electrical options, such as air-source heat pump water heaters (ASHPWH). While many studies focus on reducing space heating, research on the effectiveness of ASHPWHs in cold climates is limited. This study aims to fill that knowledge gap by analyzing the performance of ASHPWHs in typical home applications across various climates in Canada. An experimental setup was constructed, and TRNSYS modeling was employed to evaluate the techno-economic and environmental performances of these systems in comparison to existing natural gas and conventional electric water heating systems. The findings of this research indicate that ASHPWHs possess the capability to substantially decrease greenhouse gas (GHG) emissions when compared to conventional natural gas-fired water heaters. Despite this significant environmental benefit, ASHPWHs may not be the most cost-effective option due to the prevailing natural gas pricing structure. Nevertheless, there is potential for these systems to become more economically viable in the future, particularly if an appropriate level of carbon pricing mechanisms is implemented.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 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".