Techno-economic assessment of liquid carrier methods for intercontinental shipping of hydrogen: A case study
Bibliographic record
Abstract
As global economies seek to transition to low-carbon energy systems to achieve net zero targets, hydrogen has potential to play a key role to decarbonise sectors that are unsuited to electrification or where long-term energy storage is required. Hydrogen can also assist in enabling decentralized renewable power generation to satisfy higher electricity demand to match the scale-up of electrified technologies. In this context, suitable transport, storage, and distribution networks will be essential to connect hydrogen generation and utilisation sites. This paper presents a techno-economic impact evaluation of international marine hydrogen transportation between Canada and the Netherlands, comparing liquid hydrogen, ammonia, and a dibenzyl toluene liquid organic hydrogen carrier (LOHC) as potential transport vectors. Economic costs, energy consumption and losses in each phase of the transportation system were analysed for each vector. Based on the devised scenarios, our model suggests levelised costs of hydrogen of 6.35–9.49 $ 2022 /kg H2 and pathway efficiencies of 55.6–71.9%. While liquid hydrogen was identified as the most cost-competitive carrier, sensitivity analysis revealed a merit order for system optimisation strategies, based upon which LOHC could outperform both liquid hydrogen and ammonia in the future. • Comparative techno-economic analysis of large-scale, transatlantic hydrogen transport technologies. • Model suggests levelised costs of hydrogen of 6.35–9.49 $/kg and pathway efficiencies of 55.6–71.9%. • Liquid hydrogen was identified as the most suitable carrier for Canada-EU hydrogen shipping. • Improved dehydrogenation efficiencies could make LOHCs cost competitive. • Co-locating reconversion plants with industrial heat sources should be a priority for deployment.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".