An engineering model for wind turbines under yawed conditions derived from high fidelity models

An engineering model for wind turbines under yawed conditions derived from high fidelity models

Rahimi, H.
Garcia, A.M.
Stoevesandt, B.
Peinke, J.
Schepers, J.G.

2018

This work presents a significantly improved engineering model for the prediction of the loads in yawed flow. The newly developedmodel focuses on the so-called skewedwake effect. This effect leads to an azimuthal variation of the axial induction velocity which depends on the yawangle, tip speed ratio,wind speed, andradial position.Theazimuthal variationof theinduced velocities leads to a variation in blade loads, which is important for the prediction of fatigue loads and determines the yawing moment which can be stabilizing or destabilizing and is among others important for passively yawed turbines. The paper puts particular emphasis on the contribution of the root vorticity to the azimuthal variationof inducedvelocity.Current widely used models typically only take into account the skewedwake effect without the contribution of root vorticity, i.e., leading to a significant different radial dependency of the skewed wake effects. The new model is derived from computational fluid dynamics of 3 multimegawatt-class wind turbines, namely the NREL 5MW and two 10-MW turbines designed in the EU projects AVATAR and INNWIND.EU. Simulations were performed by means of an actuator linemodel. The proposed model is validated with results from a fully resolved computational fluid dynamics model, a free vortex wake code and actuator line model simulations for different wind turbines and yaw angles. The obtained results indicate that in many cases, the new model considerably improves the prediction of the azimuthal variation of axial induction factor and the resulting variation in blade loads and consequent yawing moment.

Energy Efficiency
Energy / Geological Survey Netherlands
Actuator line model
Blade element momentum
BEM
CFD
Engineering model
Skewed wake
model, yawed flow

http://resolver.tudelft.nl/uuid:bc2a0171-60ab-49d4-85f3-62a292b4ac4a

874898

TNO

Wind Energy, 21, 618-633

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