Digital twins help maintain green energy assets

How can AI-powered technology predict issues in wind turbines and other green energy plants?

Spotted: As is the case with industry in general, with most types of energy generation, downtime means less efficiency and less profit. This is especially true with wind generation, where having a wind turbine offline at the wrong time can lead to significant expense and lost profits. Climate tech startup Annea is working to reduce the downtime of wind facilities with an automated predictive maintenance platform.

Annea’s platform uses artificial intelligence (AI) to create digital twins of every component in a wind turbine. This way, the software can predict exactly what type of issues could arise and exactly when they are likely to occur. The system uses advanced machine learning and drone image recognition to enable early detection of underperformance and failures, along with accurate production forecasting.

The information provided by the platform helps teams make data-driven decisions and conduct preventive maintenance, which improves the uptime and performance of assets. Annea has already worked with more than 10,000 wind turbines, providing a large database for validation and training.

Annea recently raised $2.9 million (around €2.75 million) in seed funding and plans to use the funds to strengthen and expand its presence and partnerships in the US, Europe, and Southeast Asia.

Digital twins have been used in other recent innovations, including in a platform to aid electricity networks and a platform that assesses the climate resilience of property portfolios.

Written By: Lisa Magloff