Dependence of turbulence estimations on nacelle-lidar scanning strategies

Fu, Wei; Sebastiani, Alessandro; Peña, Alfredo; Mann, Jakob

doi:10.5194/wes-2022-85

Cited by 2 publications

(2 citation statements)

References 27 publications

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“…x + u 2 y . We do not simulate the lidar probe volume, which is important for turbulence estimations using lidars (Peña et al, 2017;Fu et al, 2022). Therefore, the radial velocities are retrieved as point measurements with a three-dimensional linear interpolation from the flow solution.…”

Section: Virtual Lidar Measurementsmentioning

confidence: 99%

A method to correct for the effect of blockage and wakes on power performance measurements

Sebastiani¹,

Bleeg²,

Peña³

2023

Preprint

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Abstract. Wind turbine power performance measurements often occur at the perimeter of a wind farm, where the wind flow is subject to blockage effects, which might impact the measured power performance. We perform Reynolds-averaged Navier-Stokes simulations of a wind farm with five rows of twenty turbines each, operating in a conventionally neutral boundary layer, to evaluate whether the power performances measured for turbines in the upstream row would differ from that of a turbine operating in isolation under the same inflow conditions. We simulate the power performance measurements with both meteorological masts and nacelle-mounted lidars. Results show that blockage effects have an impact on the measured power performance of the wind farm turbines, with measured power coefficient varying more than 1 % relative to what is measured for the isolated turbine. In this work, we propose a method to correct for the effect of blockage on power performance measurements, yielding a curve that is more consistent with how power curves in energy yield analyses are defined and used, and thereby allowing for more useful comparisons between these curves. Our numerical results indicate that the correction method greatly reduces blockage-related variance and bias in the measured power curves. While flow modelling can be used to calculate the correction factors for actual power performance measurements in the field, we additionally show how some of the correction factors can be derived from lidar measurements. Finally, the numerical results suggest that the method could also be used to correct for the effect of wakes on power performance measurements conducted on turbines located downstream of the leading row.

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Section: Virtual Lidar Measurementsmentioning

confidence: 99%

A method to correct for the effect of blockage and wakes on power performance measurements

Sebastiani¹,

Bleeg²,

Peña³

2023

Preprint

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show abstract

“…Furthermore, the bridge construction ( 6) can be reformulated to only constrain the wind field on the instantaneous radial component of the wind field available from the line-of-sight measurements from LIDAR. Therefore, a systematic reconstruction of the wind field,e .g., from SpinnerLIDAR trajectories as outlined in [23], should offer further possibilities for validating the superstatistical model.…”

Section: Reconstruction Of Spatiotemporal Wind Fields From Line-of-si...mentioning

confidence: 99%

Wind fields from atmospheric turbulence measurements

Friedrich

Peinke

2023

J. Phys.: Conf. Ser.

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We present recent advances in the modeling of wind fields and their reconstruction from real-world atmospheric turbulence measurements. The proposed wind field model provides a statistically coherent framework for modeling the empirically observed occurrence of extreme atmospheric events. Furthermore, we demonstrate that the model is general enough to enmesh real-world measurement points, e.g., from meteorological masts or LIDAR, and thus provides a rather convenient method for the reconstruction of highly resolved, three-dimensional wind fields. Our methodology is based on the so-called superstatistics of Gaussian-distributed (or Mann-type) velocity fields with fluctuating covariances and exactly reproduces higher-order statistics due to extreme small-scale wind fluctuations. Therefore, it could lead to more realistic inflow conditions and might potentially enhance the current design standard of wind turbines. We further discuss potential applications of the wind field model in the context of LIDAR measurements as well as for wake situations.

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Dependence of turbulence estimations on nacelle-lidar scanning strategies

Cited by 2 publications

References 27 publications

A method to correct for the effect of blockage and wakes on power performance measurements

A method to correct for the effect of blockage and wakes on power performance measurements

Wind fields from atmospheric turbulence measurements

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