Analysis of an Integrated Thermal Energy System for Applications in Cold Regions
Bibliographic record
Abstract
Abstract This paper performed analyses on a proposed direct wind-powered heat pump integrated with a pond which serves as an evaporator for space heating in cold regions. The analysis was conducted using environmental data for selected locations in Canada and the engineering equation solver (EES). Three different pairings of heat pumps and wind turbines were studied (a wind-powered heat pump with a pond as an evaporator, wind-powered heat pump without a pond, and an electricity-powered heat pump (EPHP)). Energy and exergy analyses were performed on the systems. The novelty in the present study is in the use of a wind turbine to directly power the heat pump and using a pond as the evaporator. The results show that the proposed system has the highest coefficient of performance (COP) compared with the others. The average coefficient of performance for the selected locations is 2.7, which is at least 67% better than the others. Similarly, the overall exergy for the proposed system is 16.9%, which is at least 40% better than the others. The average heating capacity of the selected locations for the proposed system is 4.5 kW, which is from 29% to 300% better than the others. Additionally, the sustainability index (SI) for the proposed system is the highest for the proposed system. The results have shown that the proposed system has superior overall performance for space heating in cold regions.
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 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 | 0.002 | 0.003 |
| 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".