The WinDTwin project aims to develop a digital twin platform tailored for wind farms, with a primary objective of enhancing the efficiency (optimising energy generation), increasing market participation (and associated revenue), and meeting the predictive maintenance needs (reducing downtime periods and related costs). To achieve this goal, WinDTwin evaluates current solutions and goes beyond the State-of-Art (SoA) by developing Artificial Intelligence (AI) models that address the gaps of actual tools in the market. WinDTwin will collect sensor, market, grid, weather, SCADA and security data. Then use data management expertise, machine learning (ML) algorithms and other AI techniques to create five models and three analysis tools.

WinDTwin will be able to identify the failures and performance losses, increase the market integration and support the O&M decisions by monitoring real-time data and providing secure and high-quality data assurance. Thus, the platform will provide a service that is not possible to be provided with manual controls of the wind farm operators.



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