Techno-Economic Analysis of a Solar Adsorption Cooling System for Residential Applications in Canada
Bibliographic record
Abstract
The demand for space cooling is increasing worldwide due to the increase of population as well as the rising global temperatures. This increase in demand increases the peak load distribution on the electricity grid. Solar cooling technologies such as adsorption cooling have shown to be capable at reducing and shifting the electrical loads required for cooling. In this thesis, an adsorption system was simulated and tested in various cities across Canada in order to compare its performance to conventional HVAC systems. Areas where natural gas is available for a low cost, like Saskatchewan and Alberta, were found to have a much lower economic benefit for this type of system but would receive the largest reductions in carbon dioxide emissions of all the other provinces. A solar adsorption system in Toronto was found to reduce the buildings electrical consumption, greenhouse gas emissions, and annual cost of electricity by significant amounts when compared to a waterto-water heat pump and air conditioner with electric or natural gas heating. The findings from this thesis depend on a number of factors, such as location, greenhouse gas intensity of the local electrical grid, local utility rates, and weather conditions. When using the adsorption chiller on a district heating setup, the payback period was reduced to be within the system's life expectancy and in some cases more cost effective than currently installed consumer systems. The main limiting factor for adsorption cooling is acquiring a heat source that can have a large thermal output either from solar or waste heat. Depending on the area available on the roof of a building, vacuum tube collectors may need to be used.
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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".