Study of fleet energy efficiency optimization method based on big data

Maritime transportation has been playing an important role in the global economic development. However, it brings much detrimental impact on the environment. At present, the topic of fleet optimization management for energy saving and emission reduction attracts increasing attention. The existing operation management models, which don’t consider the extreme weather condition and the influence of environment on ship energy efficiency and safety, has been difficult to meet the demand of the increasing development of the maritime transportation. Operational data analysis is an effective way to deal with this problem. However, In order to improve analysis accuracy, much more data should be analyzed and hence higher processing ability is required. Therefore, a novel big data analysis method should be proposed to address the fleet navigation optimization that considers various influencing factors comprehensively. Nowadays, the rapid development of Internet of Things and communication technology promotes explosive growth of data in the maritime transport, including environmental and operational information. These information and associated big data technology make it possible to develop such an effective energy efficiency optimization method of fleet to improve navigational safety and efficiency.

This research aims to develop an effective energy efficiency optimization method of fleet based on big data technology to improve navigational safety and efficiency. Based on the analysis of big environmental and operational data, the fleet energy efficiency optimization model could be established and the advanced optimization methods would be deployed to determine the safe and energy-efficient sailing speed and route of the entire fleet.

MPC for the fleet energy efficiency optimization

Ship naviation optimization base on big data analysis for improving energy efficiency


PhD candidate: Kai Wang, MSc
Supervisor: Dr. ir. X.L. Jiang