Estimation of Weibull distribution for wind speeds along ship routes

In order to evaluate potential benefits of new green shipping concepts that utilize wind power as auxiliary propulsion in ships or of offshore wind energy harvest, it is essential to have reliable wind speed statistics. A new method to find parameters in the Weibull distribution is given. It can be...

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Published in:Proceedings of the Institution of Mechanical Engineers, Part M: Journal of Engineering for the Maritime Environment
Main Authors: Mao, Wengang, Rychlik, Igor
Language:unknown
Published: 2017
Subjects:
Online Access:https://doi.org/10.1177/1475090216653495
https://research.chalmers.se/en/publication/242092
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author Mao, Wengang
Rychlik, Igor
author_facet Mao, Wengang
Rychlik, Igor
author_sort Mao, Wengang
collection Unknown
container_issue 2
container_start_page 464
container_title Proceedings of the Institution of Mechanical Engineers, Part M: Journal of Engineering for the Maritime Environment
container_volume 231
description In order to evaluate potential benefits of new green shipping concepts that utilize wind power as auxiliary propulsion in ships or of offshore wind energy harvest, it is essential to have reliable wind speed statistics. A new method to find parameters in the Weibull distribution is given. It can be used either at a fixed offshore position or along arbitrary ship routes. The method employs a spatio-temporal transformed Gaussian model for wind speed variability. The model was fitted to 10 years’ ERA-Interim reanalysis data of wind speed. The proposed method to derive Weibull distribution is validated using wind speeds measured on-board by vessels sailing in the North Atlantic and the west region of the Mediterranean Sea. For the westbound voyages in the North Atlantic, the proposed method gives a good approximation of the observed wind distribution along those ship routes. For the eastbound voyages, significant difference is found between the observed wind distribution and that approximated by the proposed method. The suspected reason is attributed to the ship routing decisions of masters and software. Hence, models that consider only the wind climate description need to be supplemented with a method to take into account the effect of wind-aware routing plan.
genre North Atlantic
genre_facet North Atlantic
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op_container_end_page 480
op_doi https://doi.org/10.1177/1475090216653495
op_relation http://dx.doi.org/10.1177/1475090216653495
https://research.chalmers.se/en/publication/242092
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spelling ftchalmersuniv:oai:research.chalmers.se:242092 2025-06-15T14:42:52+00:00 Estimation of Weibull distribution for wind speeds along ship routes Mao, Wengang Rychlik, Igor 2017 text https://doi.org/10.1177/1475090216653495 https://research.chalmers.se/en/publication/242092 unknown http://dx.doi.org/10.1177/1475090216653495 https://research.chalmers.se/en/publication/242092 Probability Theory and Statistics Wind speeds wind energy efficiency Weibull distribution hindcast wind on-board measurements 2017 ftchalmersuniv https://doi.org/10.1177/1475090216653495 2025-05-19T04:26:12Z In order to evaluate potential benefits of new green shipping concepts that utilize wind power as auxiliary propulsion in ships or of offshore wind energy harvest, it is essential to have reliable wind speed statistics. A new method to find parameters in the Weibull distribution is given. It can be used either at a fixed offshore position or along arbitrary ship routes. The method employs a spatio-temporal transformed Gaussian model for wind speed variability. The model was fitted to 10 years’ ERA-Interim reanalysis data of wind speed. The proposed method to derive Weibull distribution is validated using wind speeds measured on-board by vessels sailing in the North Atlantic and the west region of the Mediterranean Sea. For the westbound voyages in the North Atlantic, the proposed method gives a good approximation of the observed wind distribution along those ship routes. For the eastbound voyages, significant difference is found between the observed wind distribution and that approximated by the proposed method. The suspected reason is attributed to the ship routing decisions of masters and software. Hence, models that consider only the wind climate description need to be supplemented with a method to take into account the effect of wind-aware routing plan. Other/Unknown Material North Atlantic Unknown Proceedings of the Institution of Mechanical Engineers, Part M: Journal of Engineering for the Maritime Environment 231 2 464 480
spellingShingle Probability Theory and Statistics
Wind speeds
wind energy efficiency
Weibull distribution
hindcast wind
on-board measurements
Mao, Wengang
Rychlik, Igor
Estimation of Weibull distribution for wind speeds along ship routes
title Estimation of Weibull distribution for wind speeds along ship routes
title_full Estimation of Weibull distribution for wind speeds along ship routes
title_fullStr Estimation of Weibull distribution for wind speeds along ship routes
title_full_unstemmed Estimation of Weibull distribution for wind speeds along ship routes
title_short Estimation of Weibull distribution for wind speeds along ship routes
title_sort estimation of weibull distribution for wind speeds along ship routes
topic Probability Theory and Statistics
Wind speeds
wind energy efficiency
Weibull distribution
hindcast wind
on-board measurements
topic_facet Probability Theory and Statistics
Wind speeds
wind energy efficiency
Weibull distribution
hindcast wind
on-board measurements
url https://doi.org/10.1177/1475090216653495
https://research.chalmers.se/en/publication/242092