EOLES

EOLES is an R&D project created in consortium with TETRACE, TAES, Enhol, EO6, DasNano, Renercycle, and CENER.

In Europe, a significant part of the wind farm fleet is reaching the end of its certified service life. By 2030, 57 GW will have reached 20 years of age, with Spain being one of the countries with the oldest fleets. In Navarre, nearly 1 GW will be affected by this situation in the coming years. In this context, operators must decide whether to extend the service life of their wind farms, replace old turbines with new ones (repowering), or proceed with decommissioning. This decision-making process is a challenge, as there are no objective tools capable of assessing all relevant aspects of the different alternatives. Existing methodologies are used to estimate component degradation and failures, and while technically advanced, they are not integrated into a holistic approach that considers technical, economic, regulatory, and environmental factors. Furthermore, the absence of validation with real-world data limits their practical applicability in the effective management of wind farms at the end of their service life. This creates a gap that hinders efficient and sustainable planning of wind farms.

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EOLES proposes a solution to this challenge, and an innovation at a global level: the first tool capable of integrating all relevant inputs in this decision-making process (condition of the wind farm and its turbines, economic aspects, circularity factors, etc.) will be developed. EOLES will allow wind farm operators to simulate different end-of-life scenarios and carry out objective and realistic comparisons.

This tool will centralize operational and design data, and will integrate complex analyses of productivity, structural condition of components, impact of adverse events, and logistical needs for each end-of-life scenario. It will also provide a detailed assessment of the circularity of components and materials. By combining surrogate models and real-time data, EOLES will facilitate the generation of end-of-life scenarios, enabling accurate estimation of the progression of turbine component conditions. Moreover, it will directly address the lack of validation with real data, a critical weakness of existing methodologies. To achieve this, wind farms in Navarre with diverse ages, technologies, and capacities will be selected, ensuring the extrapolation and relevance of the results obtained.