The role of hydrogen in decarbonizing Alberta’s electricity system
Bibliographic record
Abstract
This paper explores the role that hydrogen can play in helping Alberta decarbonize its electricity system. Alberta has an abundance of natural gas resources that can be converted to hydrogen fuel and further used to generate electricity either through a turbine or through a fuel cell. Since Alberta has a significant portion of its current electricity needs supplied by combustion and steam turbines, such turbines can be repurposed to use hydrogen fuels and therefore reduce the amount of stranded assets as the province moves towards lower emissions in the electricity industry. Using hydrogen in the electricity industry can also complement a higher percentage of variable renewable energy resources, like wind and solar, by absorbing excess generation via electrolysis and providing much needed reliability as a peaking product. The carbon price and associated carbon policy in Alberta appears to be a key driver incentivizing hydrogen use in the electricity industry. Our model comparing the marginal costs of natural gas versus hydrogen for electricity production concludes that with the current carbon policy in Alberta and a rising carbon price to $170 per tonne CO2e in 2030, hydrogen has the potential to compete with natural gas as a dominant, "on-demand" power source.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".