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A Review of Predictive and Prescriptive Offshore Wind Farm Operation and Maintenance

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posted on 2025-08-01, 13:43 authored by H Fox, AC Pillai, D Friedrich, M Collu, T Dawood, L Johanning
Offshore wind farms are a rapidly developing source of clean, low-carbon energy and as they continue to grow in scale and capacity, so does the requirement for their efficient and optimised operation and maintenance. Historically, approaches to maintenance have been purely reactive. However, there is a movement in offshore wind, and wider industry in general, towards more proactive, condition based maintenance approaches which rely on operational data-driven decision making. This paper reviews the current efforts in proactive maintenance strategies, both predictive and prescriptive, of which the latter is an evolution of the former. Both use operational data to determine whether a turbine component will fail in order to provide sufficient warning to carry out necessary maintenance. Prescriptive strategies also provide optimised maintenance actions, incorporating predictions into a wider maintenance plan to address predicted failure modes. Beginning with a summary of common techniques used across both strategies, the review moves on to discuss their respective applications in offshore wind operation and maintenance. The review concludes with suggested areas for future work, underlining the need for models which can be simply incorporated by site operators and integrate live data whilst handling uncertainties. A need for further focus on medium term planning strategies is also highlighted along with consideration of the question of how to quantify the impact of a proactive maintenance strategy.

Funding

EP/S023933/1

Engineering and Physical Sciences Research Council (EPSRC)

Natural Environment Research Council (NERC)

RF\202021\20\175

Royal Academy of Engineering (RAE)

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© 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).

Notes

This is the final version. Available on open access from MDPI via the DOI in this record

Journal

Energies

Publisher

MDPI

Version

  • Version of Record

Language

en

FCD date

2022-01-11T15:10:19Z

FOA date

2022-01-11T15:32:22Z

Citation

Vol. 15 (2), article 504

Department

  • Engineering

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