Two-component wind fields from scanning aerosol lidar and motion estimation algorithms

Mayor, Satyajit; Dérian, Pierre; Mauzey, Christopher F.; Hamada, Masaki

doi:10.1117/12.2025337

Cited by 4 publications

(6 citation statements)

References 22 publications

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“…Gaussian functions (red lines) were fitted to the histograms. The modeled distribution (black lines) were computed using Equations (7) and (11). A good match for different sizes of patches are shown in the comparison between the real measured distribution and the modeled distribution.…”

Section: Improved Results Using the Modified Prediction Modelmentioning

confidence: 97%

“…The effect of the scales of the gusts needs to be considered in Equation (10) since we are modeling gusts. The details will be illustrated in Section 3, and the modified random walk theory is given in Equation (11). The modified random walk theory (Equation (11)) and the Gaussian model (Equation (7)) comprise the impact prediction model for advecting gust patches with different sizes.…”

Section: Prediction Of the Probability Of Impact Locationmentioning

confidence: 99%

“…Mayor adapted two computer-vision methods for flow motion estimation: the cross-correlation method and the wavelet-based optical flow method [10,11]. However, the cross-correlation method has limitations for non-uniform velocity fields, and the optical flow method requires relatively small (few pixels) movement and is computationally demanding.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Wind Gust Detection and Impact Prediction for Wind Turbines

Zhou

Cherukuru

Sun³

et al. 2018

Remote Sensing

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Wind gusts on a scale from 100 m to 1000 m are studied due to their significant influence on wind turbine performance. A detecting and tracking algorithm is proposed to extract gusts from a wind field and track their movement. The algorithm utilizes the "peak over threshold method," Moore-Neighbor tracing algorithm, and Taylor's frozen turbulence hypothesis. The algorithm was implemented for a three-hour, two-dimensional wind field retrieved from the measurements of a coherent Doppler lidar. The Gaussian shape distribution of the gust spanwise deviation from the streamline was demonstrated. Size dependency of gust deviations is discussed, and an empirical power function is derived. A prediction model estimating the impact of gusts with respect to arrival time and the probability of arrival locations is introduced, in which the Gaussian plume model and random walk theory including size dependency are applied. The prediction model was tested and the results reveal that the prediction model can represent the spanwise deviation of the gusts and capture the effect of gust size. The prediction model was applied to a virtual wind turbine array, and estimates are given for which wind turbines would be impacted.

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Section: Improved Results Using the Modified Prediction Modelmentioning

confidence: 97%

Section: Prediction Of the Probability Of Impact Locationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Wind Gust Detection and Impact Prediction for Wind Turbines

Zhou

Cherukuru

Sun³

et al. 2018

Remote Sensing

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“…We thank Zhou et al [1] for citing these two papers [5,6]. Their statements regarding our research results are however inaccurate and do not include the latest peer-reviewed research in the field.…”

Section: Statements In Zhou Et Al [1] About Motion Estimation Methodsmentioning

confidence: 97%

“…They chose to compute the wind fields by applying a 2D variational analysis method (2D-VAR) to radial component velocities measured by a single Doppler lidar ([1], Section 2.2). Alternative approaches to remotely observe similar 2D-2C wind fields are also mentioned in the introduction of the paper: "Mayor adapted two computer-vision methods for flow motion estimation: the cross-correlation method and the wavelet-based optical flow method [5,6]. "-(Zhou et al [1], Section 1).…”

Section: Statements In Zhou Et Al [1] About Motion Estimation Methodsmentioning

confidence: 99%

Comments on “Wind Gust Detection and Impact Prediction for Wind Turbines”

Mayor

Dérian

2018

Remote Sensing

Self Cite

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We refute statements in “Zhou, K., et al. Wind gust detection and impact prediction for wind turbines. Remote Sens. 2018, 10, 514.” the impracticality of motion estimation methods to derive two-component vector wind fields from single scanning aerosol lidar data. Our assertion is supported by recently published results on the performance of two image-based motion estimation methods: cross-correlation (CC) and wavelet-based optical flow (WOF). The characteristics and performances of CC and WOF are compared with those of a two-dimensional variational (2D-VAR) method that was applied to radial velocity fields from a single scanning Doppler lidar. The algorithmic aspects of WOF and 2D-VAR are reviewed and we conclude that these two approaches are in fact similar and practical.

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Wind retrieval from multiangle backscatter lidar profiles through anisotropic aerosol structures

Tomás

Rocadenbosch

2015

JGR Atmospheres

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A wind retrieval correlation method for backscatter lidar scanning schemes consisting of a few profiling sounding lines of sight is mathematically formulated in matrix solution form under general anisotropic atmospheric conditions and convective boundary layer scenarios. The method assumes the frozen atmosphere model and works with temporal cross-correlation functions that do not need to be maximized. The method also applies to the well-known case of slant scans based on the multiple-angle azimuth technique (horizontal wind retrievals). A first application of the method to a 1064 nm wavelength case example is presented for a 40°e levation, two-angle azimuth scan, where horizontal wind speed and wind direction are retrieved.

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Two-component wind fields from scanning aerosol lidar and motion estimation algorithms

Cited by 4 publications

References 22 publications

Wind Gust Detection and Impact Prediction for Wind Turbines

Wind Gust Detection and Impact Prediction for Wind Turbines

Comments on “Wind Gust Detection and Impact Prediction for Wind Turbines”

Wind retrieval from multiangle backscatter lidar profiles through anisotropic aerosol structures

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