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Why wind O&M needs AI grounded in physics

Published in: Wind, Exclusive Articles, Industrial Insight

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AI is becoming increasingly important in wind O&M, but data alone cannot explain why a turbine is behaving differently. Liam Sharkey, SVP of AI & Innovation at ONYX, examines why combining AI with engineering physics can provide operators with more useful answers.

As the wind industry looks for better ways to manage assets and improve the profitability of operational projects, interest in AI-powered operations & maintenance (O&M) tools has grown. Faster processing of asset data is useful, but operators also need to understand why a system has reached a particular conclusion. For wind O&M, that means combining data analysis with tools grounded in the physics of the turbine.

Operators have to balance a wide range of O&M demands. These include managing mixed OEM fleets and ageing assets, making performance and derating decisions, forecasting remaining useful life, monitoring asset health and meeting commercial obligations. They must also manage factors outside their direct control, including weather, supply chain pressure and equipment availability.

This leaves operators with plenty of opportunities to improve efficiency and has encouraged more autonomous O&M models, with operators taking greater control of maintenance activities. AI is increasingly becoming part of that approach. Major OEMs, utilities and fleet operators are already incorporating it into asset management systems to improve yield, reduce unplanned downtime and help prevent serious failures.

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