Wind Gust Characterization at Wind Turbine Relevant Heights in Moderately Complex Terrain

W. Hu Department of Earth and Atmospheric Sciences, and Sibley School of Mechanical and Aerospace Engineering, Cornell University, Ithaca, New York

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F. Letson Department of Earth and Atmospheric Sciences, and Sibley School of Mechanical and Aerospace Engineering, Cornell University, Ithaca, New York

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R. J. Barthelmie Sibley School of Mechanical and Aerospace Engineering, Cornell University, Ithaca, New York

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S. C. Pryor Department of Earth and Atmospheric Sciences, Cornell University, Ithaca, New York

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Abstract

Improved understanding of wind gusts in complex terrain is critically important to wind engineering and specifically the wind energy industry. Observational data from 3D sonic anemometers deployed at 3 and 65 m at a site in moderately complex terrain within the northeastern United States are used to calculate 10 descriptors of wind gusts and to determine the parent distributions that best describe these parameters. It is shown that the parent distributions exhibit consistency across different descriptors of the gust climate. Specifically, the parameters that describe the gust intensity (gust amplitude, rise magnitude, and lapse magnitude; i.e., properties that have units of length per time) fit the two-parameter Weibull distribution, those that are unitless ratios (gust factor and peak factor) are described by log-logistic distributions, and all other properties (peak gust, rise and lapse times, gust asymmetric factor, and gust length scale) are lognormally distributed. It is also shown that gust factors scale with turbulence intensity, but gusts are distinguishable in power spectra of the longitudinal wind component (i.e., they have demonstrably different length scales than the average eddy length scale). Gust periods at the lower measurement height (3 m) are consistent with shear production, whereas at 65 m they are not. At this site, there is only a weak directional dependence of gust properties on site terrain and land cover variability along sectorial transects, but large gust length scales and gust factors are more likely to be observed in unstable atmospheric conditions.

© 2018 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Weifei Hu, wh348@cornell.edu

Abstract

Improved understanding of wind gusts in complex terrain is critically important to wind engineering and specifically the wind energy industry. Observational data from 3D sonic anemometers deployed at 3 and 65 m at a site in moderately complex terrain within the northeastern United States are used to calculate 10 descriptors of wind gusts and to determine the parent distributions that best describe these parameters. It is shown that the parent distributions exhibit consistency across different descriptors of the gust climate. Specifically, the parameters that describe the gust intensity (gust amplitude, rise magnitude, and lapse magnitude; i.e., properties that have units of length per time) fit the two-parameter Weibull distribution, those that are unitless ratios (gust factor and peak factor) are described by log-logistic distributions, and all other properties (peak gust, rise and lapse times, gust asymmetric factor, and gust length scale) are lognormally distributed. It is also shown that gust factors scale with turbulence intensity, but gusts are distinguishable in power spectra of the longitudinal wind component (i.e., they have demonstrably different length scales than the average eddy length scale). Gust periods at the lower measurement height (3 m) are consistent with shear production, whereas at 65 m they are not. At this site, there is only a weak directional dependence of gust properties on site terrain and land cover variability along sectorial transects, but large gust length scales and gust factors are more likely to be observed in unstable atmospheric conditions.

© 2018 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Weifei Hu, wh348@cornell.edu
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  • Ágústsson, H., and H. Ólafsson, 2004: Mean gust factors in complex terrain. Meteor. Z., 13, 149155, https://doi.org/10.1127/0941-2948/2004/0013-0149.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • ASCE, 2010: Minimum Design Loads for Buildings and Other Structures. American Society of Civil Engineers, 608 pp.

  • Ashcroft, J., 1994: The relationship between the gust ratio, terrain roughness, gust duration and the hourly mean wind speed. J. Wind Eng. Ind. Aerodyn., 53, 331355, https://doi.org/10.1016/0167-6105(94)90090-6.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bardal, L. M., and L. R. Sætran, 2016: Wind gust factors in a coastal wind climate. Energy Procedia, 94, 417424, https://doi.org/10.1016/j.egypro.2016.09.207.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Beljaars, A. C. M., 1987: The influence of sampling and filtering on measured wind gusts. J. Atmos. Oceanic Technol., 4, 613626, https://doi.org/10.1175/1520-0426(1987)004<0613:TIOSAF>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bierbooms, W., 2005: Constrained stochastic simulation—Generation of time series around some specific event in a normal process. Extremes, 8, 207224, https://doi.org/10.1007/s10687-006-7968-7.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bierbooms, W., and P.-W. Cheng, 2002: Stochastic gust model for design calculations of wind turbines. J. Wind Eng. Ind. Aerodyn., 90, 12371251, https://doi.org/10.1016/S0167-6105(02)00255-6.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Boettcher, F., C. Renner, H.-P. Waldl, and J. Peinke, 2003: On the statistics of wind gusts. Bound.-Layer Meteor., 108, 163173, https://doi.org/10.1023/A:1023009722736.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Branlard, E., 2009: Wind energy: On the statistics of gusts and their propagation through a wind farm. ECN Wind Memo. 09-005, 48 pp.

  • Brasseur, O., 2001: Development and application of a physical approach to estimating wind gusts. Mon. Wea. Rev., 129, 525, https://doi.org/10.1175/1520-0493(2001)129<0005:DAAOAP>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Burton, T., N. Jenkins, D. Sharpe, and E. Bossanyi, 2011: Wind Energy Handbook. 2nd ed. John Wiley and Sons, 780 pp.

    • Crossref
    • Export Citation
  • Camp, T. R., and H.-W. Shin, 1995: Turbulence intensity and length scale measurements in multistage compressors. J. Turbomach., 117, 3846, https://doi.org/10.1115/1.2835642.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Chan, P. W., 2012: An event of tail strike of an aircraft due to terrain‐induced wind shear at the Hong Kong International Airport. Meteor. Appl., 19, 325333, https://doi.org/10.1002/met.264.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Cheng, P. W., and W. Bierbooms, 2001: Distribution of extreme gust loads of wind turbines. J. Wind Eng. Ind. Aerodyn., 89, 309324, https://doi.org/10.1016/S0167-6105(00)00084-2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Danish Society of Engineers, 1992: DS 472: Code of practice for loads and safety of wind turbine constructions. Danish Society of Engineers and the Federation of Engineers Tech. Rep., 78 pp.

  • Deaves, D. M., and R. I. Harris, 1976: A mathematical model of the structure of strong winds. Environmental Sciences Research Unit Rep. 24, 49 pp.

    • Crossref
    • Export Citation
  • Dimitrov, N., 2016: Comparative analysis of methods for modelling the short‐term probability distribution of extreme wind turbine loads. Wind Energy, 19, 717737, https://doi.org/10.1002/we.1861.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Dupont, S., D. Pivato, and Y. Brunet, 2015: Wind damage propagation in forests. Agric. For. Meteor., 214–215, 243251, https://doi.org/10.1016/j.agrformet.2015.07.010.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Durst, C. S., 1960: Wind speeds over short periods of time. Meteor. Mag., 89, 181186.

  • Engineering Sciences Data Unit, 2001: Characteristics of atmospheric turbulence near the ground. Part II: Single point data for strong winds (neutral atmosphere). ESDU Tech. Rep. 85020, 37 pp.

  • Farr, T. G., and Coauthors, 2007: The Shuttle Radar Topography Mission. Rev. Geophys., 45, RG2004, https://doi.org/10.1029/2005RG000183.

  • Frost, W., and R. E. Turner, 1982: A discrete gust model for use in the design of wind energy conversion systems. J. Appl. Meteor., 21, 770776, https://doi.org/10.1175/1520-0450(1982)021<0770:ADGMFU>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Germanischer Lloyd, 2010: Guideline for the certification of wind turbines. Germanischer Lloyd Industrial Services Tech. Rep., 389 pp.

  • Greenway, M. E., 1979: An analytical approach to wind velocity gust factors. J. Wind Eng. Ind. Aerodyn., 5, 6191, https://doi.org/10.1016/0167-6105(79)90025-4.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hogg, R. V., A. T. Craig, and J. W. McKean, 2005: Introduction to Mathematical Statistics. 6th ed. Pearson Prentice Hall, 704 pp.

  • Holmes, J. D., A. C. Allsop, and J. D. Ginger, 2014: Gust durations, gust factors and gust response factors in wind codes and standards. Wind Struct., 19, 339352, https://doi.org/10.12989/was.2014.19.3.339.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hu, W., D. Park, and D. Choi, 2013: Structural optimization procedure of a composite wind turbine blade for reducing both material cost and blade weight. Eng. Optim., 45, 14691487, https://doi.org/10.1080/0305215X.2012.743533.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hu, W., K. K. Choi, O. Zhupanska, and J. H. J. Buchholz, 2016: Integrating variable wind load, aerodynamic, and structural analyses towards accurate fatigue life prediction in composite wind turbine blades. Struct. Multidiscip. Optim., 53, 375394, https://doi.org/10.1007/s00158-015-1338-5.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hu, W., S. C. Pryor, F. Letson, J. Tytell, and R. J. Barthelmie, 2017: Investigation of gust‐seismic relationships and applications to gust detection. J. Geophys. Res. Atmos., 122, 140151, https://doi.org/10.1002/2016JD025858.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • International Electrotechnical Commission, 2005: Wind turbines—Part I: Design requirements. IEC Rep. 61400–1, 90 pp.

  • Jiang, Z., Y. Xing, Y. Guo, T. Moan, and Z. Gao, 2015: Long‐term contact fatigue analysis of a planetary bearing in a land‐based wind turbine drivetrain. Wind Energy, 18, 591611, https://doi.org/10.1002/we.1713.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Jungo, P., S. Goyette, and M. Beniston, 2002: Daily wind gust speed probabilities over Switzerland according to three types of synoptic circulation. Int. J. Climatol., 22, 485499, https://doi.org/10.1002/joc.741.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kwon, D.-K., and A. Kareem, 2009: Gust-front factor: New framework for wind load effects on structures. J. Struct. Eng., 135, 717732, https://doi.org/10.1061/(ASCE)0733-9445(2009)135:6(717).

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Larsen, G. C., and K. S. Hansen, 2004: Database on wind characteristics-analyses of wind turbine design loads. Risø National Laboratory Rep., Risø-R-1473, 83 pp.

  • Letson, F., S. C. Pryor, R. J. Barthelmie, and W. Hu, 2018: Observed gust wind speeds in the coterminous United States, and their relationship to local and regional drivers. J. Wind Eng. Ind. Aerodyn., 173, 199209, https://doi.org/10.1016/j.jweia.2017.12.008.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Li, Q. S., L. Zhi, and F. Hu, 2010: Boundary layer wind structure from observations on a 325 m tower. J. Wind Eng. Ind. Aerodyn., 98, 818832, https://doi.org/10.1016/j.jweia.2010.08.001.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Li, Y., K. Togbenou, H. Xiang, and N. Chen, 2017: Simulation of non-stationary wind velocity field on bridges based on Taylor series. J. Wind Eng. Ind. Aerodyn., 169, 117127, https://doi.org/10.1016/j.jweia.2017.07.005.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Lubitz, W. D., 2009: Effects of tower shadowing on anemometer data. Proc. 11th Americas Conf. on Wind Engineering, San Juan, PR, IAWE, http://www.iawe.org/Proceedings/11ACWE/11ACWE-Lubitz.pdf.

  • Manwell, J. F., J. G. McGowan, and A. L. Rogers, 2010: Wind Energy Explained: Theory, Design and Application. 2nd ed. John Wiley and Sons, 704 pp.

    • Crossref
    • Export Citation
  • Mason, M. S., G. S. Wood, and D. F. Fletcher, 2010: Numerical investigation of the influence of topography on simulated downburst wind fields. J. Wind Eng. Ind. Aerodyn., 98, 2133, https://doi.org/10.1016/j.jweia.2009.08.011.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Mikkelsen, T., S. E. Larsen, H. E. Jørgensen, P. Astrup, and X. G. Larsén, 2017: Scaling of turbulence spectra measured in strong shear flow near the Earth’s surface. Physica Scr., 92, 124002, https://doi.org/10.1088/1402-4896/aa91b2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Monin, A. S., and A. M. Obukhov, 1954: Basic laws of turbulent mixing in the atmosphere near the ground. Tr. Geofiz. Inst., Akad. Nauk SSSR, 24, 163187.

    • Search Google Scholar
    • Export Citation
  • Munger, J. W., H. W. Loescher, and H. Luo, 2012: Measurement, tower, and site design considerations. Eddy Covariance, M. Aubinet, T. Vesala, and D. Paple, Eds., Springer, 21–58.

    • Crossref
    • Export Citation
  • Nielsen, M., G. C. Larsen, J. Mann, S. Ott, K. S. Hansen, and B. J. Pedersen, 2003: Wind simulation for extreme and fatigue loads. Risø National Laboratory Rep. Risø-R-1437, 104 pp.

  • NOAA, 1998: Automated Surface Observing System (ASOS) user’s guide. NOAA Tech. Rep., 61 pp.

  • NOAA, 2004: Automated Surface Observing System (ASOS) release note, software version 2.79. NOAA Tech. Rep., 7 pp.

  • Oke, T. R., 1987: Boundary Layer Climates. 2nd ed. Routledge, 435 pp.

  • Pineda, N., O. Jorba, J. Jorge, and J. M. Baldasano, 2004: Using NOAA AVHRR and SPOT VGT data to estimate surface parameters: Application to a mesoscale meteorological model. Int. J. Remote Sens., 25, 129143, https://doi.org/10.1080/0143116031000115201.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Pryor, S. C., R. J. Barthelmie, N. E. Clausen, M. Drews, N. MacKellar, and E. Kjellström, 2012: Analyses of possible changes in intense and extreme wind speeds over northern Europe under climate change scenarios. Climate Dyn., 38, 189208, https://doi.org/10.1007/s00382-010-0955-3.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Simiu, E., R. Wilcox, F. Sadek, and J. J. Filliben, 2003: Wind speeds in ASCE 7 standard peak-gust map: Assessment. J. Struct. Eng., 129, 427439, https://doi.org/10.1061/(ASCE)0733-9445(2003)129:4(427).

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Solari, G., 1993: Gust buffeting. II: Dynamic alongwind response. J. Struct. Eng., 119, 383398, https://doi.org/10.1061/(ASCE)0733-9445(1993)119:2(383).

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Suomi, I., T. Vihma, S.-E. Gryning, and C. Fortelius, 2013: Wind‐gust parametrizations at heights relevant for wind energy: A study based on mast observations. Quart. J. Roy. Meteor. Soc., 139, 12981310, https://doi.org/10.1002/qj.2039.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Taylor, S. W., B. M. Wotton, M. E. Alexander, and G. N. Dalrymple, 2004: Variation in wind and crown fire behaviour in a northern jack pine–black spruce forest. Can. J. For. Res., 34, 15611576, https://doi.org/10.1139/x04-116.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Thorarinsdottir, T. L., and M. S. Johnson, 2012: Probabilistic wind gust forecasting using nonhomogeneous Gaussian regression. Mon. Wea. Rev., 140, 889897, https://doi.org/10.1175/MWR-D-11-00075.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Tieleman, H. W., 1992: Wind characteristics in the surface layer over heterogeneous terrain. J. Wind Eng. Ind. Aerodyn., 41, 329340, https://doi.org/10.1016/0167-6105(92)90427-C.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Verheij, F. J., J. W. Cleijne, and J. A. Leene, 1992: Gust modelling for wind loading. J. Wind Eng. Ind. Aerodyn., 42, 947958, https://doi.org/10.1016/0167-6105(92)90101-F.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Vickery, P. J., D. Wadhera, J. Galsworthy, J. A. Peterka, P. A. Irwin, and L. A. Griffis, 2010: Ultimate wind load design gust wind speeds in the United States for use in ASCE-7. J. Struct. Eng., 136, 613625, https://doi.org/10.1061/(ASCE)ST.1943-541X.0000145.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Welch, P., 1967: The use of fast Fourier transform for the estimation of power spectra: A method based on time averaging over short, modified periodograms. IEEE Trans. Audio Electroacoust., 15, 7073, https://doi.org/10.1109/TAU.1967.1161901.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wieringa, J., 1973: Gust factors over open water and built-up country. Bound.-Layer Meteor., 3, 424441, https://doi.org/10.1007/BF01034986.

  • WMO, 2012: Measurement of surface wind. Guide to meteorological instruments and methods of observation, WMO-No. 8, 2008 edition Updated in 2010, World Meteorological Organization.

  • Young, G. S., and L. Kristensen, 1992: Surface-layer gusts for aircraft operation. Bound.-Layer Meteor., 59, 231242, https://doi.org/10.1007/BF00119814.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Zhang, L.-L., J. Li, and Y. Peng, 2008: Dynamic response and reliability analysis of tall buildings subject to wind loading. J. Wind Eng. Ind. Aerodyn., 96, 2540, https://doi.org/10.1016/j.jweia.2007.03.001.

    • Crossref
    • Search Google Scholar
    • Export Citation
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