Abstract. The computational effort for wind turbine design load calculations is more extreme than it is for other applications (e.g., aerospace), which necessitates the use of efficient but low-fidelity models. Traditionally the blade element momentum (BEM) method is used to resolve the rotor aerodynamic loads for this purpose, as this method is fast and robust. With the current trend of increasing rotor size, and consequently large and flexible blades, a need has risen for a more accurate prediction of rotor aerodynamics. Previous work has demonstrated large improvement potential in terms of fatigue load predictions using vortex wake models together with a manageable penalty in computational effort. The present publication has contributed towards making vortex wake models ready for application to certification load calculations. The observed reduction in flapwise blade root moment fatigue loading using vortex wake models instead of the blade element momentum (BEM) method from previous publications has been verified using computational fluid dynamics (CFD) simulations. A validation effort against a long-term field measurement campaign featuring 2.5 MW turbines has also confirmed the improved prediction of unsteady load characteristics by vortex wake models against BEM-based models in terms of fatigue loading. New light has been shed on the cause for the observed differences and several model improvements have been developed, both to reduce the computational effort of vortex wake simulations and to make BEM models more accurate. Scoping analyses for an entire fatigue load set have revealed the overall fatigue reduction may be up to 5 % for the AVATAR 10 MW rotor using a vortex wake rather than a BEM-based code.
The primary objective of the MEXICO (Model Experiments in Controlled Conditions) project was to generate experimental data for validation of models for wind turbines. Kulite c pressure sensors were used for pressure measurements while Particle Image Velocimetry was used with the aim of tracking the tip vortex trajectory. The pressure measurements were carried out for both axial and yawed flow conditions with yaw angles of 15 o , 30 o and 45 o . For the Particle Image Velocimetry measurements data was gathered for axial flow and for the ±30 o yaw cases at a single tip speed ratio. In this work, an inverse free wake lifting line model, a direct free wake model and a BEM model are validated with the MEXICO data. Particular emphasis is placed on the study of yawed flow conditions. The inverse free-wake model makes use of the experimental loads as input in order to find the distribution of inductions and angle of attack. The predictive capability of BEM may therefore be assessed based on this. Validation of the inverse free-wake model was performed by investigating the stagnation pressure prediction as well as the vortex trajectory prediction. This was done by means of the PIV data gathered from the MEXICO experiment. This PIV data was also used for validation purposes of the direct free-wake model. The differences in the angle of attack distributions in yawed flow with these models was studied in order to assess the difference in results between the use of 2D and 3D airfoil data.
Abstract. Dynamic stall phenomena bring risk for negative damping and instability in wind turbine blades. It is crucial to model these phenomena accurately to reduce inaccuracies in predicting design driving (fatigue) loads. Inaccuracies in current dynamic stall models may be due to the facts that they are not properly designed for high angles of attack, and that they do not specifically describe vortex shedding behaviour. The Snel second order dynamic stall model attempts to explicitly model unsteady vortex shedding. This model could therefore be a valuable addition to DNV GL's turbine design software Bladed. In this thesis the model has been validated with oscillating airfoil experiments and improvements have been proposed for reducing inaccuracies. The proposed changes led to an overall reduction in error between the model and experimental data. Furthermore the vibration frequency prediction improved significantly. The improved model has been implemented in Bladed and tested against small scale turbine experiments at parked conditions. At high angles of attack the model looks promising for reducing mismatches between predicated and measured (fatigue) loading. Leading to possible lower safety factors for design and more cost efficient designs for future wind turbines.
Abstract. Dynamic stall phenomena carry the risk of negative damping and instability in wind turbine blades. It is crucial to model these phenomena accurately to reduce inaccuracies in predicting design driving (fatigue and extreme) loads. Some of the inaccuracies in current dynamic stall models may be due to the fact that they are not properly designed for high angles of attack and that they do not specifically describe vortex shedding behaviour. The Snel second-order dynamic stall model attempts to explicitly model unsteady vortex shedding. This model could therefore be a valuable addition to a turbine design software such as Bladed. In this paper the model has been validated with oscillating aerofoil experiments, and improvements have been proposed for reducing inaccuracies. The proposed changes led to an overall reduction in error between the model and experimental data. Furthermore the vibration frequency prediction improved significantly. The improved model has been implemented in Bladed and tested against small-scale turbine experiments at parked conditions. At high angles of attack the model looks promising for reducing mismatches between predicted and measured (fatigue and extreme) loading, leading to possible lower safety factors for design and more cost-efficient designs for future wind turbines.
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