Digital twins to revolutionise wind industry, says report

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digital twins, wind industry,
© Evgeniy Shkolenko

Digital twins promise to revolutionise the wind industry by optimising project performance and maintenance, according to a new report by Navigant Research

Digital twins can empower wind asset owners and turbine manufacturers operating wind turbines to predict and plan for faults and optimise performance of their assets, according to Navigant.

The new report by Navigant Research examines wind sector-specific offerings, trends, and an intensifying vendor landscape.

Predictive analytics and twin modelling are sweeping across many industries, including the wind sector, where wind turbines lend themselves well to collecting vast amounts of data that can inform and refine digital twin models.

Jesse Broehl, senior research analyst with Navigant Research, said: “Digital copies of operating wind turbines can enable asset owners to virtually and remotely monitor, test, and predict the performance and condition of turbines and subcomponents and carry out performance and reliability tests in a virtual environment.

“This empowers asset owners and wind turbine manufacturers operating wind turbines to predict and plan for faults and optimise performance of their assets.”

To leverage digital twin technology, the report recommends wind turbine OEMs see themselves as both vendors and customers of the technology, while independent software as service vendors mine the market and leverage third-party independence over wind turbine OEMs.

Meanwhile, asset owners implementing digital twins should test and verify the technology’s promises.

The report, ‘Advancing O&M Insights for Wind Plants with Digital Twins’, examines drivers and barriers for wind turbine asset owners, wind turbine OEMs, and software vendors that are increasingly active in this space. It also discusses specific market players using digital twin technology, applications and strategies specific to wind turbines, and provides recommendations for wind market participants.

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