Understanding costs in hydrogen infrastructure networks: A multi-stage approach for spatially-aware pipeline design

• Published in: International journal of hydrogen energy 2025-02, Vol.102, p.430-443
• Main Authors: Hammond, Joseph, Rosenberg, Manou, Brown, Solomon
• Format: Article
• Language: English
• Subjects: Genetic algorithm; GIS; Hydrogen infrastructure; Industrial clusters; Pipeline design optimisation; Pipeline routing with obstacles
• ISSN: 0360-3199
• DOI: 10.1016/j.ijhydene.2024.12.273

The emergence and design of hydrogen transport infrastructures are crucial steps towards the development of a hydrogen economy. However, pipeline routing remains underdeveloped in hydrogen infrastructure design models, despite its significant impact on the resultant cost and network configuration. Many previous studies assume uniform cost surfaces on which pipelines are designed. Studies that consider a variable cost surface focus on designing candidate networks rather than bespoke routes for a given infrastructure. This study proposes a novel multi-stage approach based on a graph-based Steiner tree with Obstacles Genetic Algorithm (StObGA) to route pipelines on a complex cost surface for multi-source multi-sink hydrogen networks. The application of StObGA results in cost savings of 20–40% compared to alternative graph-based methods that assume uniform cost surfaces. Furthermore, this publication presents an in-depth methodological comparative analysis of different pipeline routing and sizing methods used in the literature and discusses their impact. Finally, we demonstrate how this model can generate design variations and provide practical insights to inform industry and policymakers. [Display omitted] •Innovative pipeline routing design accounting for complex geographical constraints.•Infrastructure cost savings of 20–40% compared against alternative methods.•Using commercially available discrete sizes increases the cost by 4.3%.•Method is validated against real pipeline routes.