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1 September 2016 A Multisource Information System for Monitoring and Improving Ship Energy Efficiency
Ailong Fan, Xinping Yan, Qizhi Yin
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Abstract

Fan, A.; Yan, X., and Yin, Q., 2016. A multisource information system for monitoring and improving ship energy efficiency.

Global climate change has attracted an increasing amount of attention by the public. The shipping industry is being scrutinized with regard to improving efficiency and reducing emissions. This paper explores the monitoring technology and efficiency enhancement method for a ship. First, the internal and external factors that affect a ship's energy efficiency are determined and examined. Second, an inland river ship is selected as a research target on which a multisource information system is constructed via the selection and installation of the corresponding sensors on the ship. A series of system tests have also been performed when the ship is in operation. The field tests prove that the established system is adequate for the voyage and that all of the sensors can normally monitor the parameters. In addition, a massive quantity of data for the upper, middle, and lower reaches of the Yangtze River are obtained. A grey correlation analysis and regional difference analysis are conducted using these data. The analysis results suggest that the main engine speed has the greatest effect on a ship's fuel consumption and that the voyage environment of the Yangtze River affects a ship's fuel consumption. Finally, a novel ship speed-optimization method that considers the impact of voyage environment is proposed as an energy efficiency enhancement example. This study not only aids shipping companies and ship officers in monitoring a ship's operations but also provides a high-energy efficiency strategy for a ship's operation.

Ailong Fan, Xinping Yan, and Qizhi Yin "A Multisource Information System for Monitoring and Improving Ship Energy Efficiency," Journal of Coastal Research 32(5), 1235-1245, (1 September 2016). https://doi.org/10.2112/JCOASTRES-D-15-00234.1
Received: 3 December 2015; Accepted: 23 February 2016; Published: 1 September 2016
KEYWORDS
CO2 emissions
dynamic programming
EEOI
marine engine
MRV
speed optimization
voyage environment
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