Investigating the Techno-Economic and Environmental Performance of Hydrogen Deployment Paradigms in Canada
Bibliographic record
Abstract
This thesis employs simulation and optimization to conduct a multi-scale investigation of the cost and performance of two hydrogen transition pathways. Chapter 2 simulates production pathways for green hydrogen in Canada's Atlantic Maritimes. Projects could be implemented by 2050 and at <2 $/kgH2 with aggressive growth rates, learning rates, and electrolyzer capital costs of 500 $/kW. Chapter 3 develops a method to estimate the thermal loads in remote and northern communities. It applies this method to 40 communities and develops a regression model that estimates thermal loads. Chapter 4 builds an optimization model that deploys wind turbines and reversible fuel cells to meet the electrical and thermal loads of those 40 communities. This model overbuilds wind capacity. Five communities have costs of avoided emissions of <200 CAD/tCO2, while 30 have costs of <500 CAD/tCO2.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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".