WINDTRUE project starts with kick-off meeting at CWI

On 4 March our new WINDTRUE project took to the air, aiming to develop new models that help turbine designers manage large uncertainties in wind and wave behavior, which makes well-dimensioned, cost-optimal designs possible.

Publication date
27 Mar 2019

On 4 March 2019 CWI’s new WINDTRUE project took to the air. We aim to develop new models that help turbine designers manage large uncertainties in wind and wave behavior, which makes well-dimensioned, cost-optimal designs possible. Together with our partners at DNV GL, Suzlon and ECN we have now formally launched the project.

The energy production of a wind turbine is predicted with models that contain several uncertainties, due to the stochastic nature of wind and waves. Therefore it is not known exactly how reliable the model predictions are. The quantification of uncertainty in models and the propagation of uncertainties through the calculations is an active field of research.

The main objective of the WINDTRUE project is to develop calibrated aerodynamic models with a quantified level of uncertainty for optimal design of the next generation of offshore wind turbines. With these models designers can  make wind turbine designs in which uncertainties are taken into account in a structured way, giving a more reliable prediction of the service life of an offshore wind turbine. This in turn makes risk assessments for financing future offshore wind farms more precise, and consequently lowers the cost of energy. Our models with a quantified level of uncertainty will also be key in constructing digital twins of wind turbines, a novel modelling paradigm in which models and data are seamlessly integrated into a virtual environment.

A post-doc researcher working on the WINDTRUE project will start at CWI in May 2019. The project will end in December 2020. Partners are: ECN part of TNO, Suzlon Energy Limited and DNV GL Netherlands B.V. The project acronym WINDTRUE stands for: WIND Turbine Rotor aeroelasticity UncErtainty quantification.

 

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