Ship sailing speed optimization considering dynamic meteorological conditions

Sailing speed optimization is a cost-effective strategy to improve ship energy efficiency and a viable way to fulfill emission reduction requirements. This study develops a novel ship sailing speed optimization method that considers dynamic meteorological conditions. We first develop an artificial n...

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Main Authors: Luo, Xi, Yan, Ran, Wang, Shuaian
Other Authors: School of Civil and Environmental Engineering
Format: Article
Language:English
Published: 2024
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Online Access:https://hdl.handle.net/10356/180753
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1807532024-10-23T00:54:53Z Ship sailing speed optimization considering dynamic meteorological conditions Luo, Xi Yan, Ran Wang, Shuaian School of Civil and Environmental Engineering Engineering Ship energy efficiency Ship fuel consumption prediction Sailing speed optimization is a cost-effective strategy to improve ship energy efficiency and a viable way to fulfill emission reduction requirements. This study develops a novel ship sailing speed optimization method that considers dynamic meteorological conditions. We first develop an artificial neural network model for vessel fuel consumption rate (FCR) prediction based on a fusion dataset of ship noon reports and public meteorological data. Then, based on the predicted FCRs, the method repeatedly formulates a multistage graph based on the most recent forecasts, and optimal speeds for the remaining voyage are obtained until the vessel reaches the destination port. The computational efficiency of the optimization process is enhanced by progressively removing nodes without connections to successor nodes, starting from the penultimate stage. We examine the proposed method on two 11-day voyages of a dry bulk carrier. Results show that the proposed method demonstrates significant reductions in fuel consumption by 5.35% compared with a constant sailing speed scheme and by 7.34% compared with a static speed optimization model. In addition, the proposed model achieves similar fuel savings to those achieved by speed optimization based on actual meteorological conditions, enabling shipping companies to optimize ship sailing speeds in the absence of actual meteorological conditions. The proposed method can be applied to various types of vessels due to its flexibility and adaptability, making it a valuable tool for the shipping industry to reduce greenhouse gas (GHG) emissions, thereby supporting the International Maritime Organization (IMO)’s goal of reaching net-zero GHG emissions by around 2050. Ministry of Education (MOE) Nanyang Technological University This work was supported by the National Natural Science Foundation of China [Grant Nos. 72071173, 71831008], and the Research Grants Council of the Hong Kong Special Administrative Region, China [Project number HKSAR RGC TRS T32-707/22-N]. The corresponding author also acknowledges the Start-Up Grant from Nanyang Technological University, Singapore and the funding support from Singapore MOE AcRF Tier 1 Grant (RG75/23). 2024-10-23T00:54:52Z 2024-10-23T00:54:52Z 2024 Journal Article Luo, X., Yan, R. & Wang, S. (2024). Ship sailing speed optimization considering dynamic meteorological conditions. Transportation Research Part C, 167, 104827-. https://dx.doi.org/10.1016/j.trc.2024.104827 0968-090X https://hdl.handle.net/10356/180753 10.1016/j.trc.2024.104827 2-s2.0-85201604397 167 104827 en RG75/23 NTU SUG Transportation Research Part C © 2024 Elsevier Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies.
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Engineering
Ship energy efficiency
Ship fuel consumption prediction
spellingShingle Engineering
Ship energy efficiency
Ship fuel consumption prediction
Luo, Xi
Yan, Ran
Wang, Shuaian
Ship sailing speed optimization considering dynamic meteorological conditions
description Sailing speed optimization is a cost-effective strategy to improve ship energy efficiency and a viable way to fulfill emission reduction requirements. This study develops a novel ship sailing speed optimization method that considers dynamic meteorological conditions. We first develop an artificial neural network model for vessel fuel consumption rate (FCR) prediction based on a fusion dataset of ship noon reports and public meteorological data. Then, based on the predicted FCRs, the method repeatedly formulates a multistage graph based on the most recent forecasts, and optimal speeds for the remaining voyage are obtained until the vessel reaches the destination port. The computational efficiency of the optimization process is enhanced by progressively removing nodes without connections to successor nodes, starting from the penultimate stage. We examine the proposed method on two 11-day voyages of a dry bulk carrier. Results show that the proposed method demonstrates significant reductions in fuel consumption by 5.35% compared with a constant sailing speed scheme and by 7.34% compared with a static speed optimization model. In addition, the proposed model achieves similar fuel savings to those achieved by speed optimization based on actual meteorological conditions, enabling shipping companies to optimize ship sailing speeds in the absence of actual meteorological conditions. The proposed method can be applied to various types of vessels due to its flexibility and adaptability, making it a valuable tool for the shipping industry to reduce greenhouse gas (GHG) emissions, thereby supporting the International Maritime Organization (IMO)’s goal of reaching net-zero GHG emissions by around 2050.
author2 School of Civil and Environmental Engineering
author_facet School of Civil and Environmental Engineering
Luo, Xi
Yan, Ran
Wang, Shuaian
format Article
author Luo, Xi
Yan, Ran
Wang, Shuaian
author_sort Luo, Xi
title Ship sailing speed optimization considering dynamic meteorological conditions
title_short Ship sailing speed optimization considering dynamic meteorological conditions
title_full Ship sailing speed optimization considering dynamic meteorological conditions
title_fullStr Ship sailing speed optimization considering dynamic meteorological conditions
title_full_unstemmed Ship sailing speed optimization considering dynamic meteorological conditions
title_sort ship sailing speed optimization considering dynamic meteorological conditions
publishDate 2024
url https://hdl.handle.net/10356/180753
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