SHIFT – Steel & Hydrogen Integrated Freight Trade

SHIFT is a spatially resolved techno-economic optimization of global iron and steel supply chains under decarbonization. It explores how hydrogen-based direct reduced iron (DRI) production and hot-briquetted iron (HBI) trade can shift value creation to regions with renewable energy and capital availability, using a two-stage pipeline (greenfield supply curves, then cross-region LP trade) built on PyPSA and orchestrated with Snakemake.

Quick start – installation & execution

SHIFT requires Python 3.10+ and uses pixi to manage the environment. Install pixi before you continue.

git clone https://github.com/energyLS/shift.git
cd shift
pixi install
pixi run snakemake model_trade_all

Approximate runtimes:

• Installation (pixi install): ~5 minutes
• Full model (model_trade_all): ~5 hours

By default, the model solves with HiGHS, a license-free solver. If you have a Gurobi license, set solver.name: gurobi in config/config.yaml for faster solves.

Tip

For a quick, low-resolution run, check out the demo branch, which uses fewer regions and quantities and completes in ~1 hour.

Key results

model_trade_all populates results/<scenario>/ for each configured trade scenario with:

• result.csv – regional production volumes and shipped quantities
• map_ironore.pdf, map_hbi.pdf, map_steel.pdf – trade-flow maps by product
• network.nc – the full PyPSA network, for further analysis

Documentation

Full documentation - installation details, solver setup, the workflow stages, config flags, and a module-by-module reference - lives in docs/ and is built with mkdocs:

pixi run -e docs mkdocs serve

then open http://127.0.0.1:8000.

Acknowledgements

Thanks to:

• Oda Agdal and her Master's Thesis on the Investigation of Future Global Trade of Hydrogen from Renewable Energy Sources
• Johannes Hampp and TRACE

Licence

This repository is licensed under the MIT License. See LICENCE for details.