EUDP

This project addresses a critical gap in the wind industry: lack of scalable, automated diagnostic tools capable of identifying wind turbine issues before these escalate, thereby minimizing the operational downtime. An Automated Service Inspection (ASI) system will be developed and demonstrated on a Vestas V172 - 7.2MW wind turbine at Høvsøre Test Site. It will integrate stationery cameras, microphones and drone-based cameras with AI models trained on historical and real-time turbine data. These models will automatically analyze the new visual and acoustic input in combination with existing wind turbine sensors (e.g. pressure, temperature) inputs to detect early signs and specific reasons for wear, misalignment, or failure thereby reducing reliance on manual inspection and troubleshooting. 

The long-term business impact for Vestas includes reduced service technician hours pr wind turbine, fewer reactive service visits, improved safety, and increased turbine availability, ultimately boosting annual energy production. By enabling smarter, data-driven service operations this project supports Vestas’ strategic goals of operational excellence, sustainability, and leadership in digital wind energy solutions as well as EU's ambition for energy system digitalization, detailed in the 2022 EU Action Plan on Digitalizing the Energy System. 

The project has received funding from EUPD - The Energy Technology Development and Demonstration Programme.