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Green H2 Production Cost – Demonstration Model

Demonstration disclosure:
This interactive model is provided for illustrative purposes only, using representative renewable generation profiles and simplified time resolution. Commercial assessments are conducted using full 8,760-hour, location-specific profiles and extended sensitivity analysis.
  1. Green hydrogen (GH₂), typically produced through the electrolysis of water using renewable electricity, is expected to play an increasingly important role in global decarbonisation, particularly in sectors that are difficult to abate through direct electrification.

  2. This section provides a quantitative evaluation of green hydrogen production costs using an optimisation-based analytical tool. It helps assess the cost of GH₂ production under a range of assumptions, including capital and operating costs, capacity utilisation factors (CUFs) of renewable power sources, electrolyser efficiency, hydrogen storage requirements arising from renewable intermittency, and the capital recovery factor used in estimating levelised costs.
    The optimisation minimises the levelised cost of green hydrogen production

  3. Solar and wind resources are characterised by intrinsically low and time-varying CUFs. These characteristics have a significant influence on electrolyser utilisation and hydrogen storage requirements, particularly when hydrogen demand is assumed to be continuous, as is typically the case for most industrial applications.

  4. The analysis is driven by 16 user-selectable input parameters. Default values are based on current, widely referenced estimates for each parameter. Users may modify any or all inputs to explore how changes in assumptions affect the cost of green hydrogen production.

  5. This assessment is intended as a high-level, preliminary exploration to provide directional insights into cost sensitivities. Actual project-level economics will depend on a range of location-specific, technical, and commercial factors that are beyond the scope of this illustrative analysis.

User Inputs

  1. This is the target H2 production quantum. Default value of 3000 tpd is close to 1 MMTPA




  2. Default unit solar capex value is kept at US $ 400/kw of installed capacity




  3. Default unit solar opex value is kept at US $ 8/kw of installed capacity, or 2% of capex




  4. Default yearly average value of solar CUF is 22%. Model considers hourly profile using this yearly average input




  5. Default unit onshore wind capex value is kept at US $ 1000/kw of installed capacity




  6. Default unit onshore opex value is kept at US $ 20/kw of installed capacity, or 2% of capex




  7. Default yearly average value of onshore wind CUF is 35%. Model considers hourly profile using this yearly average input




  8. Default unit offshore wind capex value is kept at US $ 3000/kw of installed capacity




  9. Default unit offshore opex value is kept at US $ 75/kw of installed capacity, or 2.5% of capex




  10. Default yearly average value of offshore wind CUF is 45%. Model considers hourly profile using this yearly average input




  11. Default unit electrolyser capex value is kept at US $ 1000/kw of installed capacity




  12. Default unit electrolyser opex value is kept at US $ 30/kw of installed capacity, or 3% of capex




  13. Default unit electricity requirement is kept at 55 Kwh per kg of H2 production




  14. Default other capex value is kept at US $ 150/kw of total installed electricity capacity




  15. Default H2 storage capex value is kept at US $ 2000/kg of H2 storage. Then a 500 ton H2 storage will entail USD 1 billion of capex




  16. Default capital recovery factor value is kept at 10%




  17. (Deep dive: Capital Recovery Factor)

    Water consumption costs for electrolysis are relatively small (typically a few cents per kilogram of hydrogen) and are therefore not explicitly modelled in this illustrative assessment.
    In detailed commercial assessments, water costs can be modelled explicitly, including the impact of water sourcing and conveyance distances from the hydrogen production site.



Note: On submission, a backend optimisation routine is executed and may take approximately 10–15 seconds depending on system load.