水素燃料補給所の分布ミスで年間数千万ユーロの損失の可能性（Planned hydrogen refuelling stations may lead to millions of euros in yearly losses）

2025-08-19 チャルマース工科大学

＜関連情報＞

• https://news.cision.com/chalmers/r/planned-hydrogen-refuelling-stations-may-lead-to-millions-of-euros-in-yearly-losses,c4219857
• https://www.sciencedirect.com/science/article/pii/S0360319925019342?via%3Dihub

欧州における長距離トラックの水素需要と再充填インフラの地理空間分布 Geospatial distribution of hydrogen demand and refueling infrastructure for long-haul trucks in Europe

Joel Löfving, Selma Brynolf, Maria Grahn
International Journal of Hydrogen Energy  Available online: 18 April 2025
DOI:https://doi.org/10.1016/j.ijhydene.2025.04.257

Graphical abstract

Highlights

• Countries’ AFIR H₂-capacity may misalign with future H₂ demand from trucks.
• Showing the added H₂-capacity needed per EU country by 2050.
• Topography and speed important when modeling H₂-infrastructure location.
• Scalable model for simulating energy demand from a large number of vehicles.
• Data on modeled H₂ demand and refueling infrastructure for 2050 provided.

Abstract

Using hydrogen as a fuel is one option to reduce impact on climate and environment from heavy-duty road transportation. However, the deployment of a hydrogen refueling network is a major bottleneck. To facilitate this development, it is crucial to better understand appropriate location and sizing of hydrogen refueling stations (HRS). We present a bottom-up, geographically detailed model for simulating energy demand from long-haul hydrogen trucks and determining locations and sizes of HRSs, across all of Europe under different scenarios in 2050. The model, called SVENG, calculates weighted energy demand for network links, considering specific local conditions on each link along the route. These are used by a search algorithm for distributing demand along individual routes and simulate HRS locations and sizes. The model scales linearly, supporting large networks; for this study using 0.6 million rows of origin-destination cargo flow data on a network of 17,000 nodes. We show that the model’s novel functionality for calculating dynamic vehicle power requirements has a large impact on the distribution of fuel demand and required refueling infrastructure. Results are compared to the Alternative Fuels Infrastructure Regulation (AFIR) for 2030, showing that this legislation might require more HRS than necessary even in 2050 in some countries, unless vehicle sales increase rapidly. Other countries may need to deploy more capacity by 2050 even at lower rates of adoption.