Exploring the potential of power-to-gas concept to meet Ontario's industrial demand of hydrogen
Bibliographic record
Abstract
Hydrogen is an essential commodity in the refining and chemical industry. Hydrogen is commonly produced from the mature technology steam methane reforming (SMR), which has a drawback of releasing significant greenhouse gas emissions. The power-to-gas (PtG) concept, on the other hand, can produce green hydrogen through water electrolysis by utilizing Ontario's electricity grid powered mostly by CO2-free sources during off-peak demand. Also, PtG is a novel energy storage concept, which can effectively manage the surplus baseload generation issue encountered in the province. Therefore, this work explores the potential of implementing PtG to meet the demand of industrial hydrogen in Ontario. The paper examines the surplus power resulted from the off-peak net exports to neighboring jurisdictions and curtailed power from wind and nuclear during the years 2014-2016 as well as the surplus forecast for the next 15 years. Then, it quantifies the hydrogen volumes upon employing PtG versus the demand. The analysis shows that PtG energy storage concept has the potential to supply industrial users with the majority of the demand, particularly when making use of Ontario's available seasonal storage of depleted gas wells and salt caverns at least for the next four years.
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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 | 0.000 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".