Study on route division for ship energy efficiency optimization based on big environment data

Study on route division for ship energy efficiency optimization based on big environment data

Wang, K. (Wuhan University of Technology)
Yan, Xinping (National Engineering Research Center for Water Transport Safety (WTSC))
Yuan, Yupeng (Wuhan University of Technology)
Jiang, X. (TU Delft Transport Engineering and Logistics)
Lodewijks, G. (TU Delft Transport Engineering and Logistics)
Negenborn, R.R. (TU Delft Transport Engineering and Logistics)

Ma, Weiming (editor)

2017

In the case of the global energy crisis and the higher sound of energy saving and emission reduction, how to take effective management measures of ship energy efficiency to achieve the goal of energy saving and emission reduction, put forward a new challenge for the development of shipping technology. The application of big data technology provides a new idea for the research of ship energy efficiency optimization management. The energy efficiency management level of the operating ship can be improved by the analysis and mining of the big data. In this paper, a big data analysis platform for ship energy efficiency management based on the widely used Hadoop platform architecture is designed. Afterward, due to the huge amount of involved data on the energy efficiency management which has exceeded the processing ability of traditional solutions, the big data analysis method is used to achieve the route division according to environmental factors, thus to lay the foundation for speed optimization in different segments of a route. Finally, a simple decision-making method of optimal engine speed based on the result of route division is proposed, which could improve ship energy efficiency and hence reduce CO2 emission.

Marine vehicles
Big Data
Energy efficiency
Optimization
Environmental factors
Navigation
Algorithm design and analysis

http://resolver.tudelft.nl/uuid:8e6820e6-7443-48f7-8c8c-80fd43e480b4

https://doi.org/10.1109/ICTIS.2017.8047752

IEEE, Piscataway, NJ, USA

978-1-5386-0437-3

Proceedings of the 4th International Conference on Transportation Information and Safety (ICTIS 2017)

ICTIS 2017: 4th International Conference on Transportation Information and Safety, 2017-08-08 → 2017-08-10, Banff, Canada

Accepted Author Manuscript

Institutional Repository

conference paper

© 2017 K. Wang, Xinping Yan, Yupeng Yuan, X. Jiang, G. Lodewijks, R.R. Negenborn