A Techno-Economic Assessment of Sustainable Large Scale Hydrogen Production from Renewable and Non-Renewable Sources
Bibliographic record
Abstract
In recent times, the imperative to mitigate greenhouse gas (GHG) emissions that emanate from a multitude of sectors in the global energy economy has achieved unprecedented and widespread consensus. Depending on the energy resource and method used to produce hydrogen, it offers a compelling alternative to GHG intensive fossil-fuel based energy carriers. In this thesis, a techno-economic assessment of large scale, sustainable, hydrogen production pathways is addressed through the development of integrated techno-economic models. The hydrogen produced from the aforementioned pathways is used to displace hydrogen derived from natural gas - steam methane reforming (SMR), which dominates hydrogen supply, particularly in the bitumen upgrading industry in Western Canada, and oil refining complexes around the globe. As such, there is a considerable demand for low-GHG hydrogen production pathways that are cost competitive with SMR. Hydrogen production from wind energy, hydropower, natural gas and coal were assessed in the work carried out. In the case of wind energy, a wind-hydrogen plant with energy storage was evaluated. The hydrogen production cost from this pathway ranged from $3.37 - $15.06/kg H2, depending on the electrolyser size and whether or not existing wind farm infrastructure is used. The optimal electrolyser-battery configuration for the plant consists of 81 units of a 3496 kW (760 Nm3/hr) electrolyser and 360 MWh (60 units) of battery capacity. Additionally, it was observed that for a particular electrolyser-battery configuration, the minimum hydrogen production cost occurs when their respective capacity factors are approximately equivalent. For the hydropower-hydrogen plant the hydrogen production cost ranged from $1.18 to $5.35/kg H2, depending on the electrolyser size and the use of existing hydropower assets. The optimal plant configuration consists of 90 units of a 3496 kW (760 Nm3/h) electrolyser. In the case of coal and natural gas, integrated techno-economic models for underground coal gasification (UCG) and SMR with or without carbon capture and sequestration (CCS), were developed. The competitiveness of UCG and SMR is highly sensitive to the natural gas price. Hydrogen production from UCG without CCS ($1.92/kg H2) is slightly less competitive relative to SMR ($1.87/kg H2). Hydrogen production from UCG-CCS ($2.28/kg H2 to $2.92/kg H2) is slightly more competitive relative to SMR-CCS ($2.31/kg H2 to $2.60/kg H2). Overall, for the techno-economic conditions considered, hydrogen production from hydropower proved to be the pathway that is most competitive with SMR in Western Canada.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".