Abstract

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, this review moves on to discuss their respective applications in offshore wind operation and maintenance. This 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.

Highlights

  • College of Engineering, Mathematics and Physical Sciences, Exeter University, Penryn TR10 9FE, UK; Department of Naval Architecture, Ocean and Marine Engineering, University of Strathclyde, College of Shipbuilding Engineering, Harbin Engineering University, Harbin 150001, China

  • This review focuses on prescriptive maintenance, and restricts its attention and cited literature to offshore wind farms where more research is being carried out in this area

  • This section focuses on the advances and latest work in offshore wind predictive Condition-based maintenance (CBM), briefly discussing available failure data, data cleaning and failure diagnosis before moving onto failure prediction and prognosis

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Summary

A Review of Predictive and Prescriptive Offshore Wind Farm

Pillai 3, * , Daniel Friedrich 1 , Maurizio Collu 4 , Tariq Dawood 2 and Lars Johanning 3,5. College of Engineering, Mathematics and Physical Sciences, Exeter University, Penryn TR10 9FE, UK;. College of Shipbuilding Engineering, Harbin Engineering University, Harbin 150001, China

Review Methodology
Section 5.3: Operational O&M
Common Techniques for Offshore Wind Condition-Based Maintenance Strategies
Data-Driven Techniques
Artificial Intelligence Models
Statistical Models
Physics-Based Techniques
Stochastic Techniques
Hybrid Techniques
Offshore Wind Predictive Maintenance
Failure Data
Data Cleaning
Failure Diagnosis
Failure Prediction
Failure Prognosis
Best Practice in Predictive Maintenance
Strategic
Tactical
Operational
Prescriptive Maintenance Tools
Findings
Scope for Future Work in Predictive and Prescriptive Maintenance
Full Text
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