NUMERICAL ANALYSIS OF COUPLING A SOLAR THERMAL SYSTEM WITH GROUND SOURCE HEAT PUMP SYSTEM
Bibliographic record
Abstract
A ground source heat pump (GSHP) system utilizes a borehole heat exchanger to extract energy from the ground during the heating season and to deposit energy during the cooling season. This requires the drilling of an extended borehole, typically ranging from 100 to 200 meters in length, with a diameter of approximately 6 to 8 inches. Inside the borehole, a U-shaped tube is placed and surrounded by a grout that aids heat transfer between the tube and the surrounding soil. A heat transfer fluid, often a mixture of water and glycol, circulates through the tube to exchange heat with the ground. During the winter, the system draws energy from the ground for household space heating, while in the summer, when air conditioning is used, it expels energy from the house into the ground. In regions with heating-dominated climates, such as Canada, more energy is withdrawn from the ground during the winter than can be naturally restored during the summer. Consequently, the soil progressively cools over time, leading to reduced heat pump coefficient of performance and a decline in the overall system efficiency. This study explores a solution to this issue by integrating solar domestic hot water systems which employ solar thermal collectors to heat water for domestic purposes. These systems are relatively straightforward, consisting of solar thermal collectors, piping, pumps, a hot water tank, and controllers. The collector area is designed to deliver high solar fractions during the summer, but it typically exhibits lower efficiency in the winter. In Toronto, annual solar fraction, defined as the proportion of energy supplied by the solar thermal system to the total energy required by the load, typically range between 50-70%. This research aims to leverage solar thermal collectors for recharging the ground during the summer months. This approach enables the installation of larger collector areas, improving system performance in the winter, while simultaneously depositing excess energy into the ground during the summer. Notably, this study focuses on a single household located in Toronto, Canada, where the recommended solar thermal collector area is 10 square meters, and the borehole heat exchanger length is 150 meters. Also, it is assumed that four people are living in this house and required energy for heating and cooling of the house are 28000 and 7000 kWh per year, respectively. This approach offers a promising solution to balance seasonal heat transfer to the ground, mitigating the long-term decline in GSHP performance. The study demonstrates that by coupling the solar thermal system with the GSHP, the targeted outcomes are achievable.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 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) | 0.004 | 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".