Reliability assessment for an offshore green hydrogen production platform

For the decarbonization of the current energy supply offshore renewable energy sources are gaining increasing significance. One of the challenges is to transport the produced energy onshore. Because of the increasing capacities of offshore wind farms and their distance to the shore, the losses arising from transporting electricity also increase. Offshore hydrogen production addresses this issue and can serve as a technology to overcome this challenge. Producing hydrogen offshore requires a production platform. Such a hydrogen production platform requires large investments to be build and entails considerable risk. Therefore, it is necessary to investigate and assess the operations and availability of it. This work proposes a simulation model of an offshore hydrogen production platform using discrete event simulation. The model incorporates different components from the presented system layout and includes dependencies between the components, as well as corrective maintenance. The results show that the overall availability of PEM electrolysers stays above 94%. Our conclusion is that the failure rates have less impact on the overall availability than logistical changes like increasing the wave height threshold for human transfer onto the offshore platform. The results demonstrate that the proposed model can be used to simulate offshore platform operations under various system parameters and scenarios. These can be used to evaluate the performance and availability of individual components, as well as the platform as a whole.

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Publication Details

Journal
International Journal of Hydrogen Energy
Published
2026-09-17
DOI
https://doi.org/10.1016/j.ijhydene.2026.157529
Primary Topic
Hybrid Renewable Energy Systems
Type
article
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article

Reliability assessment for an offshore green hydrogen production platform

Arto Niemi, Frank Sill Torres, Lukas Sepulveda Clasen
International Journal of Hydrogen Energy
Hybrid Renewable Energy Systems
article

Reliability assessment for an offshore green hydrogen production platform

Arto Niemi, Frank Sill Torres, Lukas Sepulveda Clasen
article en

Abstract

For the decarbonization of the current energy supply offshore renewable energy sources are gaining increasing significance. One of the challenges is to transport the produced energy onshore. Because of the increasing capacities of offshore wind farms and their distance to the shore, the losses arising from transporting electricity also increase. Offshore hydrogen production addresses this issue and can serve as a technology to overcome this challenge. Producing hydrogen offshore requires a production platform. Such a hydrogen production platform requires large investments to be build and entails considerable risk. Therefore, it is necessary to investigate and assess the operations and availability of it. This work proposes a simulation model of an offshore hydrogen production platform using discrete event simulation. The model incorporates different components from the presented system layout and includes dependencies between the components, as well as corrective maintenance. The results show that the overall availability of PEM electrolysers stays above 94%. Our conclusion is that the failure rates have less impact on the overall availability than logistical changes like increasing the wave height threshold for human transfer onto the offshore platform. The results demonstrate that the proposed model can be used to simulate offshore platform operations under various system parameters and scenarios. These can be used to evaluate the performance and availability of individual components, as well as the platform as a whole.

International Journal of Hydrogen EnergyVol. 275
Deutsches Schifffahrtsmuseum (DE)
Affordable and clean energy
Openalex Percentile: Top 23%
Hybrid Renewable Energy Systems
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Reliability assessment for an offshore green hydrogen production platform — Arto Niemi, Frank Sill Torres, et al. · International Journal of Hydrogen Energy (2026) | TGRS Research Map | TGRS