Risk-based screening of green hydrogen investability: Tariffs, network charges, and de-risking in Costa Rica and the UK

Description

Data and code repository supporting the UK-CR green hydrogen analysis. Includes curated input data, reproducibility scripts, figures, tables, documentation, workflow descriptions, and manifests required to reproduce the results reported in the associated manuscript.

Steps to reproduce

Download the repository folder. Install the required Python packages: numpy, pandas, matplotlib, seaborn, scikit-learn, openpyxl, xgboost, lightgbm, and shap. Before running the workflow, check that the scripts in CODE/ point to the local repository folders rather than the original author-machine paths. Local paths should refer to DATA/, TABLES/, FIGURES/, and OUTPUT_MANIFEST/. Run the scripts in the following order: 1. CODE/01_dynamic_costa_rica.py 2. CODE/02_dynamic_uk.py 3. CODE/03_lcoh_costa_rica.py 4. CODE/04_lcoh_uk.py 5. CODE/05_npv_costa_rica.py 6. CODE/06_npv_uk.py 7. CODE/07_ml_costa_rica.py 8. CODE/08_ml_uk.py 9. CODE/09_lcoh_sensitivity_costa_rica.py 10. CODE/10_lcoh_sensitivity_uk.py 11. CODE/11_make_figure1_lcoh.py 12. CODE/12_make_figure2_npv.py 13. CODE/13_make_figure3_ml.py 14. CODE/14_make_figure4_sensitivity.py The TABLES/ folder contains expected tabular outputs, and the FIGURES/ folder contains the expected manuscript figures. File provenance, copied-file locations, and checksums are documented in OUTPUT_MANIFEST/deposit_file_manifest.xlsx. The documentation files in DOCUMENTATION/ describe the repository structure and workflow.

Institutions

• Chongqing University

  Chongqing, Chongqing

Categories

Licence