Probabilistic access forecasting for improved offshore operations

Gilbert, C., Browell, J. and McMillan, D. (2021) Probabilistic access forecasting for improved offshore operations. International Journal of Forecasting, 37(1), pp. 134-150. (doi: 10.1016/j.ijforecast.2020.03.007)

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Improving access is a priority in the offshore wind sector, driven by the opportunity to increase revenues, reduce costs, and improve safety at operational wind farms. This paper describes a novel method for producing probabilistic forecasts of safety-critical access conditions during crew transfers. Methods of generating density forecasts of significant wave height and peak wave period are developed and evaluated. It is found that boosted semi-parametric models outperform those estimated via maximum likelihood, as well as a non-parametric approach. Scenario forecasts of sea-state variables are generated and used as inputs to a data-driven vessel motion model, based on telemetry recorded during 700 crew transfers. This enables the production of probabilistic access forecasts of vessel motion during crew transfer up to 5 days ahead. The above methodology is implemented on a case study at a wind farm off the east coast of the UK.

Item Type:Articles
Additional Information:This work is supported by the EPSRC Supergen Wind Hub project ORACLES, EP/L014106/1.
Glasgow Author(s) Enlighten ID:Browell, Dr Jethro
Authors: Gilbert, C., Browell, J., and McMillan, D.
College/School:College of Science and Engineering > School of Mathematics and Statistics > Statistics
Journal Name:International Journal of Forecasting
ISSN (Online):1872-8200
Published Online:12 May 2020
Copyright Holders:Copyright © 2020 The Authors
First Published:First published in International Journal of Forecasting 37(1): 134-150
Publisher Policy:Reproduced under a Creative Commons License

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