Energy, Economic, and Environmental Assessment of an Energy Pile-Based Solar-Assisted Residential Ground Source Heat Pump System in a Canadian Cold Climate
Bibliographic record
Abstract
Abstract The building sector’s high energy consumption and related emissions signify the urgency for cleaner space conditioning technologies. While ground source heat pumps (GSHPs) and solar-assisted ground source heat pumps (SAGSHPs) offer cleaner and more efficient solutions, their wide adoption is hindered by the high initial costs. This study investigates the energy, economic, and environmental aspects of energy pile-based GSHP and SAGSHP systems in a Canadian cold climate. A finite volume numerical model of the energy pile is developed, validated and coupled with a realistic building energy load profile and photovoltaic/thermal solar collector model to evaluate the energy performance of the systems. The economic and environmental performance of the system is compared with two conventional space conditioning technologies, i.e. electric baseboard heater + air conditioner and natural gas furnace + air conditioner. The results indicate that the payback period of the GSHP and the SAGSHP systems is in the range of 6–17 years when the ground heat exchanger is incorporated into the building foundation during construction. This highlights the potential of energy piles to drastically cut down the initial cost of ground-coupled heat pump systems. Moreover, based on Alberta’s grid emission factors as of 2023, the GSHP and SAGSHP systems lower emissions by 50.2–68.2% and 88.6–91.8% compared to baseboard heater + air conditioner and 47.6–66.6% and 82.1–87.2 % compared to natural gas furnace + air conditioner, respectively.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".