Hydrogen Supply Chain Optimisation (MILP/Pyomo) — Seeking Energy System Modelling Collaborators

Hello everyone,

I am working on optimisation models for hydrogen supply chains using Mixed Integer Linear Programming (MILP) implemented in Python with Pyomo.

The model focuses on planning hydrogen infrastructure and system configuration, including:

  • electrolyser capacity expansion
  • hydrogen storage sizing
  • transport network decisions (pipelines or other transport modes)
  • demand satisfaction across locations
  • cost minimisation of the overall system

The aim is to explore infrastructure planning and system design for emerging hydrogen economies and energy transition scenarios.

I am interested in collaborating with researchers or practitioners working on:

  • energy system modelling
  • hydrogen infrastructure planning
  • techno-economic analysis of hydrogen systems
  • open datasets for energy systems
  • integration with larger energy system models (for example PyPSA, OSeMOSYS, or similar frameworks)

If anyone is working on related modelling problems or datasets, I would be happy to exchange ideas or explore potential collaboration.

I can also share the model structure or repository if there is interest.

Best regards
Gordhan