Author
Listed:
- Dinh, Quang Vu
- Dinh, Van Nguyen
- Leahy, Paul G.
Abstract
Green hydrogen, generated from renewable electricity, offers a means of decarbonising energy demand currently met by liquid and gaseous fossil fuels. However, this will require the roll-out of new technologies in diverse and distributed energy demand sectors. Therefore, the growth of hydrogen demand will depend on the rate of technological uptake in each sector. A bottom-up analytical method based on the Bass diffusion model is used to predict future hydrogen demand from the industrial, transport, power generation, and residential sectors. This is coupled with a dynamic model of green hydrogen supply based on offshore wind energy. Three scenarios for hydrogen demand in Ireland are developed and analysed as a case study. By 2050, Ireland's annual hydrogen demand is projected to reach approximately 500,000 tonnes, 950,000 tonnes, and 1,480,000 tonnes under low, medium, and high demand scenarios, respectively. To meet this demand solely through offshore wind-powered electrolysis, respective wind capacities of 5.2 GW, 9.8 GW, and 15.2 GW would be required. Future hydrogen demand is expected to mainly come from industry and zero-carbon power generation. The levelised cost of hydrogen will decline significantly as the first 500 MW of wind capacity is installed, driven by increased production scale. A sharp increase in hydrogen demand is predicted after 2030, highlighting the importance of timely infrastructure development and supportive policy frameworks. This approach highlights the gap between policy ambitions and the pace of technology diffusion, showing the potential to develop new large-scale demand sectors such as production of ammonia and sustainable aviation fuel.
Suggested Citation
Dinh, Quang Vu & Dinh, Van Nguyen & Leahy, Paul G., 2025.
"A diffusion model approach to forecast multi-sector demand growth for green hydrogen generated from offshore wind power,"
Renewable and Sustainable Energy Reviews, Elsevier, vol. 223(C).
Handle:
RePEc:eee:rensus:v:223:y:2025:i:c:s1364032125007117
DOI: 10.1016/j.rser.2025.116038
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