Editorial Type:
Article
Article Type:
Research Article

Can Wind Lidars Measure Turbulence?

A. Sathe Faculty of Aerospace Engineering, Section Wind Energy, Delft University of Technology, Delft, Netherlands

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J. Mann Wind Energy Division, Risø DTU, Roskilde, Denmark

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J. Gottschall Wind Energy Division, Risø DTU, Roskilde, Denmark

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M. S. Courtney Wind Energy Division, Risø DTU, Roskilde, Denmark

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Print Publication:
01 Jul 2011
DOI:
https://doi.org/10.1175/JTECH-D-10-05004.1
Page(s):
853–868
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Abstract

Modeling of the systematic errors in the second-order moments of wind speeds measured by continuous-wave (ZephIR) and pulsed (WindCube) lidars is presented. These lidars use the conical scanning technique to measure the velocity field. The model captures the effect of volume illumination and conical scanning. The predictions are compared with the measurements from the ZephIR, WindCube, and sonic anemometers at a flat terrain test site under different atmospheric stability conditions. The sonic measurements are used at several heights on a meteorological mast in combination with lidars that are placed on the ground. Results show that the systematic errors are up to 90% for the vertical velocity variance, whereas they are up to 70% for the horizontal velocity variance. For the ZephIR, the systematic errors increase with height, whereas for the WindCube, they decrease with height. The systematic errors also vary with atmospheric stability and are low for unstable conditions. In general, for both lidars, the model agrees well with the measurements at all heights and under different atmospheric stability conditions. For the ZephIR, the model results are improved when an additional low-pass filter for the 3-s scan is also modeled. It is concluded that with the current measurement configuration, these lidars cannot be used to measure turbulence precisely.

Corresponding author address: A. Sathe, L & R, Section Wind Energy, TU Delft, Kluyverweg 1, 2629 HS Delft, Netherlands. E-mail: a.r.sathe@tudelft.nl

Abstract

Modeling of the systematic errors in the second-order moments of wind speeds measured by continuous-wave (ZephIR) and pulsed (WindCube) lidars is presented. These lidars use the conical scanning technique to measure the velocity field. The model captures the effect of volume illumination and conical scanning. The predictions are compared with the measurements from the ZephIR, WindCube, and sonic anemometers at a flat terrain test site under different atmospheric stability conditions. The sonic measurements are used at several heights on a meteorological mast in combination with lidars that are placed on the ground. Results show that the systematic errors are up to 90% for the vertical velocity variance, whereas they are up to 70% for the horizontal velocity variance. For the ZephIR, the systematic errors increase with height, whereas for the WindCube, they decrease with height. The systematic errors also vary with atmospheric stability and are low for unstable conditions. In general, for both lidars, the model agrees well with the measurements at all heights and under different atmospheric stability conditions. For the ZephIR, the model results are improved when an additional low-pass filter for the 3-s scan is also modeled. It is concluded that with the current measurement configuration, these lidars cannot be used to measure turbulence precisely.

Corresponding author address: A. Sathe, L & R, Section Wind Energy, TU Delft, Kluyverweg 1, 2629 HS Delft, Netherlands. E-mail: a.r.sathe@tudelft.nl
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  • Banakh, V. A., Smalikho I. N. , Köpp F. , and Werner C. , 1995: Representativeness of wind measurements with a CW Doppler lidar in the atmospheric boundary layer. Appl. Opt., 34, 2055–2067.

    • Search Google Scholar
    • Export Citation

  • Banta, R. M., Newsom R. K. , Lundquist J. K. , Pichugina Y. L. , Coulter R. L. , and Mahrt L. , 2002: Nocturnal low-level jet characteristics over Kansas during CASES-99. Bound.-Layer Meteor., 105, 221–252.

    • Search Google Scholar
    • Export Citation

  • Browning, K. A., and Wexler R. , 1968: The determination of kinematic properties of a wind field using a Doppler radar. J. Appl. Meteor., 7, 105–113.

    • Search Google Scholar
    • Export Citation

  • Citriniti, J. H., and George W. K. , 1997: The reduction of spatial aliasing by long hot-wire anemometer probes. Exp. Fluids, 23, 217–224.

    • Search Google Scholar
    • Export Citation

  • Courtney, M., Wagner R. , and Lindelow P. , 2008: Testing and comparison of lidars for profile and turbulence measurements in wind energy. Proc. 14th Int. Symp. for the Advancement of Boundary Layer Remote Sensing, Vol. 1, Risø DTU, Denmark, IOP Conference Series: Earth and Environmental Science, 012021.

    • Search Google Scholar
    • Export Citation

  • Eberhard, W. L., Cupp R. E. , and Healy K. R. , 1989: Doppler lidar measurements of profiles of turbulence and momentum flux. J. Atmos. Oceanic Technol., 6, 809–819.

    • Search Google Scholar
    • Export Citation

  • Emeis, S., Harris M. , and Banta R. M. , 2007: Boundary-layer anemometry by optical remote sensing for wind energy applications. Meteor. Z., 16, 337–347, doi:10.1127/0941-2948/2007/0225.

    • Search Google Scholar
    • Export Citation

  • Engelbart, D. A. M., Kallistratova M. , and Kouznetsov R. , 2007: Determination of the turbulent fluxes of heat and momentum in the ABL by ground-based remote-sensing techniques (a review). Meteor. Z., 16, 325–335, doi:10.1127/0941-2948/2007/0224.

    • Search Google Scholar
    • Export Citation

  • Gal-Chen, T., Xu M. , and Eberhard W. L. , 1992: Estimation of atmospheric boundary layer fluxes and other turbulence parameters from Doppler lidar data. J. Geophys. Res., 97 (D17), 18 409–18 423.

    • Search Google Scholar
    • Export Citation

  • Genz, A. C., and Malik A. A. , 1980: An adaptive algorithm for numerical integration over an n-dimensional rectangular region. J. Comput. Appl. Math., 6 (4), 295–302.

    • Search Google Scholar
    • Export Citation

  • Gryning, S.-E., Batchvarova E. , Brümmer B. , Jørgensen H. , and Larsen S. , 2007: On the extension of the wind profile over homogeneous terrain beyond the surface layer. Bound.-Layer Meteor., 124, 251–268, doi:10.1007/s10546-007-9166-9.

    • Search Google Scholar
    • Export Citation

  • IEC, 2005a: Wind turbines—Part I: Design requirements. International Electrotechnical Commission IEC 61400-1, 92 pp.

  • IEC, 2005b: Offshore wind turbines—Part I: Design requirements. International Electrotechnical Commission IEC 61400-3, 136 pp.

  • IEC, 2005c: Wind turbines—Part 12-1: Power performance measurements of electricity producing wind turbines. International Electrotechnical Commission IEC 61400-12-1, 90 pp.

    • Search Google Scholar
    • Export Citation

  • Kaimal, J. C., and Finnigan J. J. , 1994: Acquisition and processing of atmospheric boundary layer data. Atmospheric Boundary Layer Flows, Oxford University Press, 255–257.

    • Search Google Scholar
    • Export Citation

  • Kindler, D., Oldroyd A. , Macaskill A. , and Finch D. , 2007: An eight month test campaign of the QinetiQ ZephIR system: Preliminary results. Meteor. Z., 16 (5), 479–489, doi:10.1127/0941-2948/2007/0226.

    • Search Google Scholar
    • Export Citation

  • Kropfli, R. A., 1986: Single Doppler radar measurement of turbulence profiles in the convective boundary layer. J. Atmos. Oceanic Technol., 3, 305–314.

    • Search Google Scholar
    • Export Citation

  • Lenschow, D. H., Mann J. , and Kristensen L. , 1994: How long is long enough when measuring fluxes and other turbulence statistics? J. Atmos. Oceanic Technol., 11, 661–673.

    • Search Google Scholar
    • Export Citation

  • Lindelöw, P., 2007: Fibre based coherent lidars for remote wind sensing. Ph.D. thesis, Technical University Denmark, 164 pp.

  • Lindelöw-Marsden, P., 2007: UpWind D1: Uncertainties in wind assessment with LIDAR. Risø DTU Tech. Rep. Risø-R-1681(EN), 55 pp.

    • Search Google Scholar
    • Export Citation

  • Mann, J., 1994: The spatial structure of neutral atmospheric surface-layer turbulence. J. Fluid Mech., 273, 141–168.

  • Mann, J., Pena A. , Bingöl F. , Wagner R. , and Courtney M. S. , 2010: Lidar scanning of momentum flux in and above the surface layer. J. Atmos. Oceanic Technol., 27, 792–806.

    • Search Google Scholar
    • Export Citation

  • Mann, J., and Coauthors, 2009: Comparison of 3D turbulence measurements using three staring wind lidars and a sonic anemometer. Meteor. Z., 18 (2), 135–140, doi:10.1127/0941-2948/2009/0370.

    • Search Google Scholar
    • Export Citation

  • Monin, A. S., and Yaglom A. M. , 1975: Statistical Fluid Mechanics. Vol. 2. MIT Press, 886 pp.

  • Motta, M., and Barthelmie R. J. , 2005: The influence of non-logarithmic wind speed profiles on potential power output at Danish offshore sites. Wind Energy, 8, 219–236.

    • Search Google Scholar
    • Export Citation

  • Peña, A., Gryning S.-E. , and Mann J. , 2010: On the length scale of the wind profile. Quart. J. Roy. Meteor. Soc., 136 (653), 2119–2131.

    • Search Google Scholar
    • Export Citation

  • Peña, A., Hasager C. B. , Gryning S.-E. , Courtney M. , Antoniou I. , and Mikkelsen T. , 2009: Offshore wind profiling using light detection and ranging measurements. Wind Energy, 12, 105–124, doi:10.1002/we.283.

    • Search Google Scholar
    • Export Citation

  • Pichugina, Y. L., Banta R. M. , Kelly N. D. , Jonkman B. J. , Tucker S. C. , Newsom R. K. , and Brewer W. A. , 2008: Horizontal-velocity and variance measurements in the stable boundary layer using Doppler lidar: Sensitivity to averaging procedures. J. Atmos. Oceanic Technol., 25, 1307–1327.

    • Search Google Scholar
    • Export Citation

  • Sjöholm, M., Mikkelsen T. , Mann J. , Enevoldsen K. , and Courtney M. , 2009: Spatial averaging-effects on turbulence measured by a continuous-wave coherent lidar. Meteor. Z., 18 (3), 281–287, doi:10.1127/0941-2948/2009/0379.

    • Search Google Scholar
    • Export Citation

  • Smalikho, I., Kopp F. , and Rahm S. , 2005: Measurement of atmospheric turbulence by 2- μm Doppler lidar. J. Atmos. Oceanic Technol., 22, 1733–1747.

    • Search Google Scholar
    • Export Citation

  • Smith, D. A., Harris M. , Coffey A. S. , Mikkelsen T. , Jørgensen H. E. , Mann J. , and Danielian R. , 2006: Wind lidar evaluation at the Danish wind test site in Høvsøre. Wind Energy, 9, 87–93, doi:10.1002/we.193.

    • Search Google Scholar
    • Export Citation

  • Sonnenschein, C. M., and Horrigan F. A. , 1971: Signal-to-noise relationships for coaxial systems that heterodyne backscatter from atmosphere. Appl. Opt., 10, 1600–1604.

    • Search Google Scholar
    • Export Citation

  • Wagner, R., Mikkelsen T. , and Courtney M. , 2009: Investigation of turbulence measurements with a continuous wave, conically scanning lidar. Risø DTU Tech. Rep. Risø-R-1682(EN), 22 pp.

    • Search Google Scholar
    • Export Citation

  • Wilson, D. A., 1970: Doppler radar studies of boundary layer wind profiles and turbulence in snow conditions. Proc. 14th Conf. on Radar Meteorology, Tucson, AZ, Amer. Meteor. Soc., 191–196.

    • Search Google Scholar
    • Export Citation

  • Wyngaard, J. C., 1968: Measurement of small-scale turbulence structure with hot wires. J. Sci. Instrum., 1, 1105–1108.

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