File(s) under permanent embargo
Development of a two-stage ship fuel consumption prediction and reduction model for a dry bulk ship
journal contribution
posted on 2023-05-20, 14:03 authored by Yan, R, Wang, S, Yuquan DuShipping industry is the backbone of global trade. However, the large quantities of greenhouse gas emissions from shipping, such as carbon dioxide (CO2), cannot be ignored. In order to comply with the international environmental regulations as well as to increase commercial profits, shipping companies have stronger motivations to improve ship energy efficiency. In this study, a two-stage ship fuel consumption prediction and reduction model is proposed for a dry bulk ship. At the first stage, a fuel consumption prediction model based on random forest regressor is proposed and validated. The prediction model takes into account ship sailing speed, total cargo weight, and sea and weather conditions and then predicts hourly fuel consumption of the main engine. The mean absolute percentage error of the random forest regressor is 7.91%. At the second stage, a speed optimization model is developed based on the prediction model proposed at the first stage while guaranteeing the estimated arrival time to the destination port. Numerical experiment on two consecutive-8-day voyages shows that the proposed model can reduce ship fuel consumption by 2–7%. The reduction in ship fuel consumption will also lead to lower CO2 emissions.
History
Publication title
Transportation Research Part E: Logistics and Transportation ReviewVolume
138Article number
101930Number
101930Pagination
1-22ISSN
1366-5545Department/School
Australian Maritime CollegePublisher
Pergamon-Elsevier Science LtdPlace of publication
The Boulevard, Langford Lane, Kidlington, Oxford, England, Ox5 1GbRights statement
© 2020 Elsevier Ltd. All rights reserved.Repository Status
- Restricted