Improving O&M decision tools for offshore wind farm vessel routing by incorporating weather uncertainty

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dc.contributor.authorHadjoudj, Yannis
dc.contributor.authorPandit, Ravi Kumar
dc.date.accessioned2023-03-21T16:15:18Z
dc.date.available2023-03-21T16:15:18Z
dc.date.issued2023-02-24
dc.description.abstractThe growth of offshore wind farms depends significantly on how well offshore wind turbines (OWTs) are operated and maintained in the long term. The operation and maintenance (O&M) activities for offshore wind are relatively more challenging due to uncertain environmental conditions than onshore and due to this, vessel routing for offshore on-site repair is remain complex and unreliable. Here, an improved data-driven decision tool is proposed to robust the vessel routing for O&M tasks under numerous environmental conditions. A novel data-driven technique based on operational datasets is presented to incorporate weather uncertainties, such as wind speed, wave period and wave height (significantly influence offshore crew repair works), into the O&M decision-making process. Results show: (1) The inclusion of weather conditions improves the O&M model uncertainty and accuracy, (2) the implementation of a model allowing weather conditions to evolve has been added to vary the probabilities of successful transfers throughout the day, and (3) the reduction of risk of transfer failure by 15%. These conclusions are further supported by the performance error metrics and uncertainty calculations. Last but not least, by generating a variety of policies for consideration, this tool gave wind turbine operators a systematic and transparent way to evaluate trade-offs and enable choices pertaining to offshore O&M. The full paper highlights the strengths and weaknesses of the proposed technique for offshore vessel routing as well as how the environmental conditions affect them.en_UK
dc.identifier.citationHadjoudj Y, Pandit RK. (2023) Improving O&M decision tools for offshore wind farm vessel routing by incorporating weather uncertainty. IET Renewable Power Generation, Volume 17, Issue 6, 27 April 2023, pp. 1488-1499en_UK
dc.identifier.issn1752-1416
dc.identifier.urihttps://doi.org/10.1049/rpg2.12689
dc.identifier.urihttps://dspace.lib.cranfield.ac.uk/handle/1826/19335
dc.language.isoenen_UK
dc.publisherIET - The Institution of Engineering and Technologyen_UK
dc.rightsAttribution 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.subjectWind turbinesen_UK
dc.subjectO&Men_UK
dc.subjectvessel routingen_UK
dc.subjectMachine learningen_UK
dc.subjectweather uncertaintyen_UK
dc.titleImproving O&M decision tools for offshore wind farm vessel routing by incorporating weather uncertaintyen_UK
dc.typeArticleen_UK

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