ALBERT

Description: This paper presents a method for obtaining the free inflow velocities from a 3D flow sensor mounted on the blade of a wind turbine. From its position on the rotating blade, e.g. one third from the tip, a blade mounted flow sensor (BMFS) is able to provide valuable information about the turbulent sheared inflow in different regions of the rotor. At the rotor, however, the inflow is affected by the wind turbine, and in most cases the wind of interest is the inflow that the wind turbine is exposed to; i.e. the free inflow velocities. The current method applies a combination of aerodynamic models and procedures to estimate the induced velocities, i.e. the disturbance of the flow field caused by the wind turbine. These velocities are subtracted from the flow velocities measured by the BMFS to obtain the free inflow velocities. Aeroelastic codes, like HAWC2, typically use a similar approach to calculate the induction, but they use it for the reversed process, i.e. they add the induction to the free inflow to get the flow velocities at the blades which are required to calculate the resulting aerodynamic forces. The aerodynamic models included in the current method comprise blade-element-momentum (BEM) based models for axial and tangential induction, a radial induction model and tip loss correction as well as models for skew and dynamic inflow. It is shown that the method is able to calculate the free inflow velocities with high accuracy when applied to aeroelastic HAWC2 simulations with a stiff structural model while some deviations are seen in simulations with a flexible structure. Furthermore, the method is tested on simulations performed by a flexible structural model coupled with a large eddy simulation (LES) flow solver. The results of this higher fidelity verification confirm the HAWC2-based conclusion.

Description: We show that the up-scaling of wind turbines from rotor diameters of 15–20 m to presently large rotors of 150–200 m has changed the requirements for the aerodynamic Blade Element Momentum (BEM) models in the aeroelastic codes. This is because the typical scales in the inflow turbulence are now comparable with the rotor diameter of the large turbines. Therefore the spectrum of the incoming turbulence relative to the rotating blade has increased energy content on 1P, 2P, ..., nP and the annular mean induction approach in a classical BEM implementation might no longer be a good approximation for large rotors. We present a complete BEM implementation on a polar grid that models the induction response to the considerable 1P, 2P, ..., nP inflow variations, including models for yawed inflow, dynamic inflow and radial induction. At each time step in an aeroelastic simulation the induction derived from a local BEM approach is updated at all the stationary grid points covering the swept area so the model can be characterized as an engineering actuator disc (AD) solution. The induction at each grid point varies slowly in time due to the dynamic inflow filter but the rotating blade now samples the induction field; as a result the induction seen from the blade is highly unsteady and has a spectrum with distinct 1P, 2P, ..., nP peaks. The load impact mechanism from this unsteady induction is analyzed and it is found that the load impact strongly depends on the turbine design and operating conditions. For operation at low to medium thrust coefficients (conventional turbines at above rated wind speed or low induction turbines in the whole operating range) it is found that the grid BEM gives typically 8–10 % lower 1 Hz fatigue loads than the classical annular mean BEM approach. At high thrust coefficients the grid BEM can give slightly increased fatigue loads. In the paper the implementation of the grid based BEM is described in detail and finally several validation cases are presented.

Description: This article qualitatively shows the yaw stability of a free-yawing downwind turbine and the ability of the turbine to align passively with the wind direction using a model with 2 degrees of freedom. An existing model of a Suzlon S111 upwind 2.1 MW turbine is converted into a downwind configuration with a 5∘ tilt and a 3.5∘ downwind cone angle. The analysis shows that the static tilt angle causes a wind-speed-dependent yaw misalignment of up to −19∘ due to the projection of the torque onto the yaw bearing and the skewed aerodynamic forces caused by wind speed projection. With increased cone angles, the yaw stiffness can be increased for better yaw alignment and the stabilization of the free-yaw motion. The shaft length influences the yaw alignment only for high wind speeds and cannot significantly contribute to the damping of the free-yaw mode within the investigated range. Asymmetric flapwise blade flexibility is seen to significantly decrease the damping of the free-yaw mode, leading to instability at wind speeds higher than 19 m s−1. It is shown that this additional degree of freedom is needed to predict the qualitative yaw behaviour of a free-yawing downwind wind turbine.

Description: In this paper, inflow information is extracted from a measurement database and used for aeroelastic simulations to investigate if using more accurate inflow descriptions improves the accuracy of the simulated wind-turbine fatigue loads. The inflow information is extracted from nearby meteorological masts (met masts) and a blade-mounted five-hole pitot tube. The met masts provide measurements of the inflow at fixed positions some distance away from the turbine, whereas the pitot tube measures the inflow while rotating with the rotor. The met mast measures the free-inflow velocity; however the measured turbulence may evolve on its way to the turbine, pass beside the turbine or the mast may be in the wake of the turbine. The inflow measured by the pitot tube, in comparison, is very representative of the wind that acts on the turbine, as it is measured close to the blades and also includes variations within the rotor plane. Nevertheless, this inflow is affected by the presence of the turbine; therefore, an aerodynamic model is used to estimate the free-inflow velocities that would have occurred at the same time and position without the presence of the turbine. The inflow information used for the simulations includes the mean wind speed field and trend, the turbulence intensity, the wind-speed shear profile, atmospheric stability-dependent turbulence parameters, and the azimuthal variations within the rotor plane. In addition, instantaneously measured wind speeds are used to constrain the turbulence. It is concluded that the period-specific turbulence intensity must be used in the aeroelastic simulations to make the range of the simulated fatigue loads representative for the range of the measured fatigue loads. Furthermore, it is found that the one-to-one correspondence between the measured and simulated fatigue loads is improved considerably by using inflow characteristics extracted from the pitot tube instead of using the met-mast-based sensors as input for the simulations. Finally, the use of pitot-tube-recorded wind speeds to constrain the inflow turbulence is found to significantly decrease the variation of the simulated loads due to different turbulence realizations (seeds), whereby the need for multiple simulations is reduced.

Description: In this paper, inflow information is extracted from a measurement database and used for aeroelastic simulations to investigate if using more accurate inflow descriptions improves the accuracy of the simulated fatigue loads. The inflow information is extracted from the nearby met masts and a blade-mounted five-hole pitot tube. The met masts provide measurements of the inflow at fixed positions some distance away, whereas the pitot tube measures the inflow while rotating with the rotor. The met mast measures the free-inflow velocity, but the measured turbulence may evolve on its way to the turbine, pass besides the turbine, or the mast may be in the wake of the turbine. The inflow measured by the pitot tube, on the other hand, is very representative of the wind that acts on the turbine as it is measured close to the blades and includes variations within the rotor plane. This inflow is, however, affected by the presence of the turbine, and therefore an aerodynamic model is used to estimate the free-inflow velocities that would have been at the same time and position without the presence of the turbine. The inflow information used for the simulations includes the mean wind speed and trend, the turbulence intensity, wind shear profile, atmospheric stability dependent turbulence parameters, and azimuthal variations within the rotor plane. In addition, the instantly measured wind speed is used to constrain the turbulence. It is concluded that the period-specific turbulence intensity must be included in the aeroelastic simulations to make the range of the simulated fatigue loads representative for the range of the measured fatigue loads. Furthermore, it is found that the one-to-one correspondence between the measured and simulated fatigue loads is improved considerably by using inflow characteristics extracted from the pitot tube instead of the met-mast-based sensors as input for the simulations. Finally, the use of pitot-tube wind speed to constrain the turbulence is found to decrease the variation of the simulated loads due to different turbulence realisations (seeds), such that the need for multiple simulations is reduced.

Description: We show that the upscaling of wind turbines from rotor diameters of 15–20 m to presently large rotors of 150–200 m has changed the requirements for the aerodynamic blade element momentum (BEM) models in the aeroelastic codes. This is because the typical scales in the inflow turbulence are now comparable with the rotor diameter of the large turbines. Therefore, the spectrum of the incoming turbulence relative to the rotating blade has increased energy content on 1P, 2P, …, nP, and the annular mean induction approach in a classical BEM implementation might no longer be a good approximation for large rotors. We present a complete BEM implementation on a polar grid that models the induction response to the considerable 1P, 2P, …, nP inflow variations, including models for yawed inflow, dynamic inflow and radial induction. At each time step, in an aeroelastic simulation, the induction derived from a local BEM approach is updated at all the stationary grid points covering the swept area so the model can be characterized as an engineering actuator disk (AD) solution. The induction at each grid point varies slowly in time due to the dynamic inflow filter but the rotating blade now samples the induction field; as a result, the induction seen from the blade is highly unsteady and has a spectrum with distinct 1P, 2P, …, nP peaks. The load impact mechanism from this unsteady induction is analyzed and it is found that the load impact strongly depends on the turbine design and operating conditions. For operation at low to medium thrust coefficients (conventional turbines at above rated wind speed or low induction turbines in the whole operating range), it is found that the grid BEM gives typically 8 %–10 % lower 1 Hz blade root flapwise fatigue loads than the classical annular mean BEM approach. At high thrust coefficients that can occur at low wind speeds, the grid BEM can give slightly increased fatigue loads. In the paper, the implementation of the grid-based BEM is described in detail, and finally several validation cases are presented. Comparisons with blade loads from full rotor CFD, wind tunnel experiments and a field experiment show that the model can predict the aerodynamic forces in half-wake, yawed flow, dynamic inflow and turbulent inflow conditions.

Description: This paper presents a method for obtaining the free-inflow velocities from a 3-D flow sensor mounted on the blade of a wind turbine. From its position on the rotating blade, e.g. one-third from the tip, a blade-mounted flow sensor (BMFS) is able to provide valuable information about the turbulent sheared inflow in different regions of the rotor. At the rotor, however, the inflow is affected by the wind turbine, and in most cases the wind of interest is the inflow that the wind turbine is exposed to, i.e. the free-inflow velocities. The current method applies a combination of aerodynamic models and procedures to estimate the induced velocities, i.e. the disturbance of the flow field caused by the wind turbine. These velocities are subtracted from the flow velocities measured by the BMFS to obtain the free-inflow velocities. Aeroelastic codes, like HAWC2, typically use a similar approach to calculate the induction, but they use it for the reversed process, i.e. they add the induction to the free inflow to get the flow velocities at the blades, which are required to calculate the resulting aerodynamic forces. The aerodynamic models included in the current method comprise models based on blade element momentum (BEM) for axial and tangential induction, a radial induction model and tip loss correction, and models for skew and dynamic inflow. It is shown that the method is able to calculate the free-inflow velocities with high accuracy when applied to aeroelastic HAWC2 simulations with a stiff structural model while some deviations are seen in simulations with a flexible structure. Furthermore, the method is tested on simulations performed by a flexible structural model coupled with a large-eddy simulation (LES) flow solver. The results of this higher-fidelity verification confirm the HAWC2-based conclusion.