Electricity supply configurations for green hydrogen hubs: A European case study on decarbonizing urban transport
Bibliographic record
Abstract
In this study, a techno-economic analysis tool for conducting detailed feasibility studies on the deployment of green hydrogen hubs for fuel cell bus fleets is developed. The study evaluates and compares five green hydrogen hub configurations' operational and economic performance under a typical metropolitan bus fleet refuelling schedule. Each configuration differs based on its electricity sourcing characteristics such as the mix of energy sources, capacity sizing, financial structure, and grid interaction. A detailed comparative analysis of distinct green hydrogen hub configurations for decarbonising a fleet of fuel-cell buses is conducted. Among the key findings is that a hybrid renewable electricity source and hydrogen storage are essential for cost-optimal operation across all configurations. Furthermore, bi-directional grid-interactive configurations are the most cost-efficient and can benefit the electricity grid by flattening the duck curve. Lastly, the paper highlights the potential for cost reduction when the fleet refuelling schedule is co-optimized with the green hydrogen hub electricity supply configuration. • Techno-economic analysis tool for a green hydrogen hub is developed. • Comparative analysis of five electricity supply configurations. • Comparison of green hydrogen economics across 5 cities in Europe. • Influence of Capex, wholesale electricity prices, and PPA price on LCOH. • A hybrid photovoltaic-wind-grid system with hydrogen storage is cost-optimal.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".