A data-driven vessel motion model for offshore access forecasting

Ciaran Gilbert, Jethro Browell, David McMillan

Research output: Chapter in Book/Report/Conference proceedingConference contribution book

4 Citations (Scopus)
23 Downloads (Pure)


Access forecasting for offshore wind farm operations is concerned with the prediction of conditions during transfer of personnel between offshore structures and vessels. Currently dispatch/scheduling decisions are typically made on the basis of single-valued forecasts of significant wave height from a numerical weather prediction model. The aim of this study is to move beyond the significant wave height metric using a data-driven methodology to estimate vessel motion during transfer. This is because turbine access is constrained by the behaviour of crew transfer vessels and the transition piece in the local wave climate. Using generalised additive models for location, scale, and shape, we map the relationship between measured vessel heave motion and measured wave conditions in terms of significant wave height, peak wave period, and peak wave direction. This is explored via a case study where measurements are collected via vessel telemetry and an on-site wave buoy during the construction phase of an east coast offshore wind farm in the UK. Different model formulations are explored and the best performing trained model, in terms of the Akaike Information Criterion, is defined. Operationally, this model is driven by temporal scenario forecasts of the input wave buoy measurements to estimate the vessel motion during transfer up to 5 days ahead.
Original languageEnglish
Title of host publicationOCEANS 2019 - Marseille
Place of PublicationPiscataway, NJ.
Number of pages6
ISBN (Electronic)9781728114507
ISBN (Print)9781728114514
Publication statusPublished - 19 Oct 2019
EventIEEE Oceans 2019 - Marseille, France
Duration: 17 Jun 201920 Jun 2019


ConferenceIEEE Oceans 2019
Internet address


  • offshore wind
  • offshore operations
  • offshore access
  • additive models
  • forecasting
  • weather prediction
  • wind power


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