Low carbon shipping

Low carbon shipping: A decision support tool for the implementation of CO₂ reducing measures

van den Berg, Seb (TU Delft Mechanical, Maritime and Materials Engineering)

Hopman, J.J. (mentor)
Kana, A.A. (mentor)
Harmsen, Jorrit (mentor)
Atasoy, B. (graduation committee)

Delft University of Technology

Marine Technology

2018-11-01

In April 2018, the International Maritime Organization (IMO) agreed upon the target to reduce the CO₂ emissions from international shipping in 2050 by 50 percent with respect to 2008 levels. The strategy to reach this target consists of the ambition to reduce CO₂ emissions per transport work, as an average across international shipping, by at least 40% by 2030, compared to 2008 levels. However, due to uncertainties involved in the decision making on the implementation of CO₂ reducing measures, shipowners are uncertain which actions to take regarding their existing fleet in order to deal with those upcoming requirements.
For rail transport, road transport and inland waterway transport, TNO has developed the Multi-level Energy Optimization tool (MEO). For these modalities, MEO is capable of calculating the CO₂ emissions for a certain voyage and assessing the effect of CO₂ reducing measures on the carbon footprint of those voyages. The objective of the research presented in this report is to extend TNO's MEO tool with the maritime modality and develop a tool supporting shipowners in the decision making process regarding the pathway of implementing CO₂ reducing measures in sea-going vessels.
The tool presented in this report is developed to meet this objective and is based on a Markov Decision Processes (MDP) model. The MDP method has the ability of optimizing a time dependent decision policy in the face of uncertainty. In this case, the optimal policy resulting from the MDP model is optimized to obtain the highest cost savings by implementing CO₂ reducing measures. For the input of the model, the vessel has to be described by an operational profile and the vessel and engine specifics such as a speed-load curve and the propulsive efficiency. Also, the environment has to be described by fuel properties, economical parameters and a regulatory framework. With this input, the MDP method can assess the optimal policy regarding the implementation of a set of CO₂ reducing measures with the objective of minimizing costs. The output of the tool consists of the expected values of total costs, CO₂ emissions and CO₂ efficiency for when the optimal policy is followed, in comparison to maintain the business as usual.

To put this tool in practice, a case study has been carried out on a 93000 DWT bulk carrier of which operational data has been provided by the shipowner. A data analysis on the daily reports of the vessel has been done to obtain the values for the vessel input and literature has been used for the environment input. The optimal policy for a set of measures is assessed and the influence on the results by varying fuel prices, the regulatory framework and the dry dock schedule has been studied. The key result of the case study is that with the implementation of several fuel saving measures and a dual fuel engine the total costs with respect to maintaining the business as usual is expected to be reduced by 12%. Also, the total accumulated carbon emission reduction over 15 years is expected to be 29% and the CO₂ efficiency is improved by 45% without having to reduce the speed of the vessel.

Maritime
Low carbon shipping
CO2 reduction
Markov Decision Processes
Decision support tool

http://resolver.tudelft.nl/uuid:b758d9f7-63a0-4ba0-ba97-d7345f46a38e

Student theses

master thesis

© 2018 Seb van den Berg