Dynamic optimization of ship energy efficiency considering time-varying environmental factors

Dynamic optimization of ship energy efficiency considering time-varying environmental factors

Wang, K. (TU Delft Transport Engineering and Logistics; Wuhan University of Technology)
Yan, Xinping (Wuhan University of Technology; MOST)
Yuan, Yupeng (Wuhan University of Technology; University of Cambridge)
Jiang, X. (TU Delft Transport Engineering and Logistics)
Lin, X. (TU Delft Transport Engineering and Logistics)
Negenborn, R.R. (TU Delft Transport Engineering and Logistics)

2018

Nowadays, optimization of ship energy efficiency attracts increasing attention in order to meet the requirement for energy conservation and emission reduction. Ship operation energy efficiency is significantly influenced by environmental factors such as wind speed and direction, water speed and depth. Owing to inherent time-variety and uncertainty associated with these various factors, it is very difficult to determine optimal sailing speeds accurately for different legs of the whole route using traditional static optimization methods, especially when the weather conditions change frequently over the length of a ship route. Therefore, in this paper, a novel dynamic optimization method adopting the model predictive control (MPC) strategy is proposed to optimize ship energy efficiency accounting for these time-varying environmental factors. Firstly, the dynamic optimization model of ship energy efficiency considering time-varying environmental factors and the nonlinear system model of ship energy efficiency are established. On this basis, the control algorithm and controller for the dynamic optimization of ship energy efficiency (DOSEE) are designed. Finally, a case study is carried out to demonstrate the validity of this optimization method. The results indicate that the optimal sailing speeds at different time steps could be determined through the dynamic optimization method. This method can improve ship energy efficiency and reduce CO₂ emissions effectively.

Dynamic optimization
Energy conservation and emission reduction
Model predictive control
Ship energy efficiency
Speed optimization

http://resolver.tudelft.nl/uuid:3d57c515-a297-474b-a91d-73a1b7583d17

https://doi.org/10.1016/j.trd.2018.04.005

2018-11-01

1361-9209

Transportation Research. Part D: Transport & Environment, 62, 685-698

Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.

Institutional Repository

journal article

© 2018 K. Wang, Xinping Yan, Yupeng Yuan, X. Jiang, X. Lin, R.R. Negenborn