Plain-language summary
- What it solves
- Hydrogen is much discussed, but the real costs of the three production routes are rarely compared.
- Who it can serve
- Anyone assessing hydrogen projects, and anyone teaching techno-economic analysis.
- What it produces
- The cost of each route and the price thresholds at which one becomes cheaper than another.
Compare industrial hydrogen routes reproducibly without mixing observed prices, scenarios and plant assumptions.
3 · What it produces
Variable cost, modelled LCOH, operational intensity, CO₂/power/gas/PPA thresholds and sensitivities.
The cards expose multiple views of the same workflow so result, method, evidence and history remain distinct.
4 · How it works
Physical balance + prices + carbon policy + sensitivity
1EEX→BFE TTF with quality/provenance gate, Italian bidding-zone day-ahead power via Energy-Charts→euenergy/ENTSO-E, EUA and grid-carbon-intensity scenario; typed HHV/LHV SMR/CCS/electrolysis parameters
2deterministic calculation; Current Variable Cost and LCOH; state-aware break-even
3physical/dimensional invariants, sourcing coherence, lineage, snapshot replay
4Persistence, rendering and governed publishing.
5 · Data and signals
| Element | Detail |
|---|---|
| Data and signals | EEX→BFE TTF with quality/provenance gate, Italian bidding-zone day-ahead power via Energy-Charts→euenergy/ENTSO-E, EUA and grid-carbon-intensity scenario; typed HHV/LHV SMR/CCS/electrolysis parameters |
| Industrial transferability | route economics, make-or-buy scenarios and decarbonisation |
| Research | emissions boundaries, sensitivity and break-even robustness |
| Interpretation condition | PPA is a scenario; no site-specific cost representation |
deterministic calculation; Current Variable Cost and LCOH; state-aware break-even
physical/dimensional invariants, sourcing coherence, lineage, snapshot replay
Python, NumPy, pandas, SciPy, Matplotlib, SQLite, PyYAML
mistaking PPA scenarios or mismatched emissions boundaries for observed facts
Workflow technical dossier
Methods, checks, stack and transferability conditions.
Data and signals
EEX→BFE TTF with quality/provenance gate, Italian bidding-zone day-ahead power via Energy-Charts→euenergy/ENTSO-E, EUA and grid-carbon-intensity scenario; typed HHV/LHV SMR/CCS/electrolysis parameters
Inference / calculation
deterministic calculation; Current Variable Cost and LCOH; state-aware break-even
Validation
physical/dimensional invariants, sourcing coherence, lineage, snapshot replay
Stack
Python, NumPy, pandas, SciPy, Matplotlib, SQLite, PyYAML
Limitations
mistaking PPA scenarios or mismatched emissions boundaries for observed facts
See recent outputs
The Publications page collects local previews and, on request, the public feed.
Potential transferability
Have a problem similar to Hydrogen Route Observatory?
A first discussion can start from the objective, available data and success criterion without sending confidential information. A result observed here is not assumed to transfer automatically to another context.