The International Maritime Organization (IMO) established new strategies that could lead to a significant reduction in the carbon footprint of the shipping sector to address global warming. A major factor in achieving this goal is transitioning to renewable fuels. This implies a challenge, as not only ship-innovative solutions but also a complete low-carbon fuel supply chain must be implemented. This work provides a method enabling the exploration of the potential of low-carbon fuel technologies for specific shipping routes up to larger sea regions. Several aspects including vessel sizes, impact of weather and shipping routes, emissions savings and costs are considered. The local energy use is determined with proven bottom-up prediction methods based on ship positioning data from the Automatic Identification System (AIS) in combination with weather and ship technical data. This methodology was extended by an approach to the generation of a basic low-carbon fuel system topology that enables the consideration of local demand profiles. The applicability of the proposed approach is discussed at hand via a case study on Roll-on/Roll-off passenger and cargo (RoPax) ferries transitioning from conventional fuels to a compressed hydrogen fuel system. The results indicate a potential reduction in emissions by up to 95% and possible system sizes and costs.

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This paper presents an estimate for the mass of hydrogen that would be needed to power the current fleet of Crew Transport Vessels (CTVs) used for maintaining the German offshore wind farms and how this demand may be geographically distributed. The estimate is based on a calculation of the marine diesel oil consumption of the current fleet, which is further employed for estimating the current emissions of these activities. Based on the predicted price of hydrogen, bunkering the CTV fleet with hydrogen may become economically advantageous in the future. Moreover, using hydrogen may reduce CO2 emissions. Results have been obtained by using vessel position data, weather data, and diesel consumption estimates. As a shortcoming, certain effects are excluded from the current estimate. However, this work presents an approach that can be improved and used for estimating hydrogen consumption in future scenarios. In these scenarios, a vessel type and parameters can be set. While here the challenge was to create a generic model that can be applied to multiple types of vessels.