The research paper, currently published in the Journal of Marine Science and Engineering, introduces a data-based energy management method for vessels.
This method enables the prediction of upcoming load demands by utilizing weather information and data from the vessel's automated tracking system. The investigated cruise ship is powered by a hybrid propulsion system, comprising a high-temperature solid oxide fuel cell covering the base load and is coupled with a battery system that compensates for the fuel cell's limited dynamic response capability in load fluctuations.
The developed energy management method predicts future load demand by analyzing physical relationships and utilizing operational as well as positional data from a real vessel. This management method facilitates a more stable operation of the fuel cell by reducing stress factors that could lead to accelerated aging of solid oxide fuel cells and therefore enhancing the resource efficiency of the propulsion system.
As large ships record tracking data during their cruises and no a priori training is required to adjust the energy management, the proposed method can be implemented under real conditions with minimal additional computational effort. The functionality of the energy management method was verified using data from a real ship and records of water currents in the North Sea. The accuracy of the load prediction is 2.7%, and the attenuation of the fuel cell's power output could be increased by approximately 32%.
For more details, refer to the article in Volume 11, 2023 of the Journal of Marine Science and Engineering, which is openly accessible.
The article was written by Cem Ünlübayir, Ulrich Hermann Mierendorff, Martin Florian Börner, Katharina Lilith Quade, Alexander Blömeke, Florian Ringbeck and Dirk Uwe Sauer
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This project has received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement No 861647.
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NAUTILUS is a short for Nautical Integrated Hybrid Energy System for Long-haul Cruise Ships.
This project has received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement No 861647.