Optimization of cold climate air-air heat pump sizing using simulation data
Bibliographic record
Abstract
Appropriate sizing and selection are crucial to maximize the energy and cost savings potential of air-to-air heat pumps (ASHPs). This is especially true for cold-climate variable capacity air-to-air heat pumps (ccASHPs), which are able to adapt their performance according to the loads of the building across a broad range of ambient conditions. Proper system sizing depends on factors such as climate, building thermal loads, and heat pump performance characteristics. Incorrect sizing can result in comfort issues, poor performance, and higher-than-expected utility costs, hindering their adoption in the residential market.This paper extends a previous study presented at the ASHRAE HVAC Cold Climate Conference 2023 which analyzed optimal ccASHP sizing and its impact on annual heating consumption in seven major Canadian cities. While this provided a strong initial insight, further information was needed on various locations across Canada, and a greater variety of housing constructions. This paper expands the research by including cooling in the analysis and expanding the number of locations to better represent Canada’s diverse climates. Improvements have also been made to the input database to better represent the Canadian building stock, including more accurate region and vintage specific envelope performance data.The analysis utilizes an in-house tool based on the TRNSYS software, enabling the generation and simulation of numerous scenarios. This tool leverages Type 660 models, which employ a resistance-capacitance approach to provide a computationally efficient alternative to detailed building modelling in TRNSYS (i.e., Type 56). The building model is further enhanced by integrating it with a custom data-driven model that better represents the impacts of cycling and defrost.The study includes a sensitivity analysis to evaluate the savings potential of ccASHPs, varying building geometry to represent five typical single-family homes across 564 locations, and three construction types based on housing vintage/construction code adoption and province-specific values. The analysis examines two configurations (central and ductless systems). For each ccASHP, ten different rated cooling capacities, ranging from half a ton to five tons, are evaluated to determine the impact of optimal sizing.Results examine the annual energy, utility cost, and greenhouse gas savings achieved by installing various ccASHPs in typical single-family homes across Canada. These findings offer valuable insights for optimizing heat pump performance and promoting their adoption in cold-climate regions, and can be used by stakeholders as a starting point for stakeholders for sizing and selection specific to their given context.
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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 | 0.001 | 0.002 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".