This result provides tools for Diagnosis and Prognosis of wind turbine corrosion, based on continuous measurements of the tower wall thickness and on predictive models. It gives the user an efficient overview of relevant data to support the decision-making process on maintenance and decommissioning. Furthermore it includes a novel control algorithm for wind turbines that allows to reduce tower loading based on its corrosion status.
Key features:
- Current and future levels of corrosion are accurately assessed thanks to real-time measurements and predictive models.
- Corrosion data is visually represented in a user-friendly way on a CAD model of the wind turbine.
- Prognosis of the remaining useful life (RUL) of the wind turbine.
- Support on the decision of the turbine decommissioning, based on the minimal levelized cost of electricity.
- Wind turbine control algorithm with optimal tradeoff between power production and tower load minimization.
- Integration with numerical weather prediction models, in order to validate the wind turbine control algorithm.
Oceans, seas and watersAddressing target audiences and expressing needs
- Use of research Infrastructure
- Collaboration
Currently, we are looking for operational WT data or research infrastructure with the aim to validate the WT diagnostic, prognostic and control tools in more real environments and achieve a higher TRL (from TRL5 to TRL7-8). Additionally, we are open to actively collaborate with companies, research institutes and universities to improve the current tools for WT applications and to extend their applicability to other domains.
- Research and Technology Organisations
R&D, Technology and Innovation aspects
Use the results and tools developed as background for new project proposals, also looking outside the offshore industry to diagnosis and prognosis of rotating machinery.
Contact potential interested customers within the FMAKE network to trigger interest in the outcome of the WATEREYE concept and find common ground.
Disseminate current scientific results and attract new partners for TUD for funding opportunities.
