An Empirically Grounded Approach to Forecast the Cost of Electrolysers (collection)

An Empirically Grounded Approach to Forecast the Cost of Electrolysers

DOI:10.4121/82988dc7-099b-45e2-81e2-3850cee1b940.v3

The DOI displayed above is for this specific version of this collection, which is currently the latest. Newer versions may be published in the future. For a link that will always point to the latest version, please use
DOI: 10.4121/82988dc7-099b-45e2-81e2-3850cee1b940

Datacite citation style

van Eijden, Bram (2025): An Empirically Grounded Approach to Forecast the Cost of Electrolysers. Version 3. 4TU.ResearchData. collection. https://doi.org/10.4121/82988dc7-099b-45e2-81e2-3850cee1b940.v3

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Collection

Version 3 - 2025-07-08 (latest)

Version 2 - 2025-07-07 Version 1 - 2025-07-07

Keywords

capacity capex Electrolysis forecasting method Renewable energy

by Bram van Eijden

This collection consists of the complete dataset and all code files developed and used for the thesis Forecasting Costs Electrolysers: An Empirically Grounded Approach to Forecast the Cost of Electrolysers. It includes the input data containing historical deployment and cost information used for model calibration and validation, as well as the Python code that implements the probabilistic S-curve deployment forecasts, the stochastic Wright’s Law cost projections, and the evaluation procedures such as external scenario comparison and hindcasting. In addition, detailed documentation is provided to facilitate replication and enable further research or policy analysis. All components of this collection are openly available to support transparency, reproducibility, and reuse in academic research and policy studies. Users are free to share, adapt, and build upon the material, provided appropriate credit is given.