The Strict Relationship Between Surface Turbulence Intensity and Wind Shear Coefficient Daily Courses: A Novel Method to Extrapolate Wind Resource to the Turbine Hub Height

Year 2015, Volume: 5 Issue: 1, 183 - 200, 01.03.2015

Giovanni Gualtieri

Abstract

Based on power law, a novel method is proposed to extrapolate surface wind speed (v) to the wind turbine (WT) hub height, via prediction of the wind shear coefficient (WSC) daily course, by only using the surface turbulence intensity (I) daily course. Work’s main outcome is a strict (almost 1:1) relationship between WSC and I daily courses which was found after applying a linear regression analysis. Practical usefulness of this finding for wind energy applications is straightforward, as merely using I values routinely collected at surface heights a WSC predicting model may be used to fairly estimate energy yield at WT hub height.A 2–year (2012–2013) dataset from the meteorological mast of Cabauw (Netherlands) was used, including 10–min records collected at heights of 10, 20, 40, and 80 m. Methods were trained over a 1–year period (2012) and then validated over an independent 1–year period (2013). WT hub heights of 40 and 80 m have been targeted for the extrapolation, being accomplished based on I observations at two surface levels: 10 and 20 m.As a result, good scores were returned by the proposed method over the most challenging height intervals: between 10 and 80 m, a 5% mean bias was achieved in extrapolated v values and at worst a 11.51% in calculated energy yield; between 20 and 80 m, extrapolated v values were biased by 2%, while energy output at worst by 6.62%.

Keywords

Wind resource extrapolation; Power law; Wind shear coefficient; Turbulence intensity; Daily course; Wind energy yield

References

• M. Motta, R.J. Barthelmie, P. Vİlund, “The influence of non–logarithmic wind speed profiles on potential power output at Danish offshore sites”, Wind Energy, Vol. 8, pp. 219–236, 2005.
• G. Gualtieri, “Surface turbulence intensity as a predictor of extrapolated wind resource to the turbine hub height”, Renewable Energy, Vol. 78, pp. 68–81,
• F. Castellani, A. Vignaroli, E. Piccioni, “Wind shear investigation performance assessment”, Journal of Energy, Vol. 4, No. 12, pp. 1–8, 2010. wind turbine
• E. Fırtın, Ö. Güler, S.A. Akdağ, “Investigation of wind shear coefficients and their effect on electrical energy generation”, Applied Energy, Vol. 88, pp. 4097–4105, 2011.
• R.J. Barthelmie, S.T. Frandsen, M.N. Nielsen, S.C. Pryor, P.–E. Rethore, H.E. Jİrgensen, “Modelling and measurements of power losses and turbulence intensity in wind turbine wakes at Middelgrunden offshore wind farm”, Wind Energy, Vol. 10, pp. 517– 528, 2007.
• D.L. Elliot, J.B. Cadogan, “Effects of wind shear and turbulence on wind turbine power curves”, European Community Wind Energy Conference and Exhibition , Madrid, Spain, Sep. 1990.
• E. Rareshide, A. Tindal, C. Johnson, A.M. Graves, E. Simpson, J. Bleeg, T. Harris, D. Schoborg, “Effects of complex wind regimes on turbine performance”, AWEA Windpower Conference, Chicago, US, May 2009.
• T. Burton, D. Scarpe, N. Jenkins, E. Bossanyi, Wind Energy Handbook , Chichester, UK: John Wiley & Sons, 2001.
• Z.O. Olaofe, K.A. Folly. “Statistical Analysis of Wind Resources at Darling for Energy Production”, Int. J. Renewable Energy Research, Vol. 2, No. 2, pp. 250– 261, 2012.
• C.G. Justus, W.R. Hargraves, A. Mikhail, D. Graber, “Methods for estimating wind speed frequency distributions”, Journal of Applied Meteorology, Vol. 17, pp. 350–353, 1977.
• T.P. Chang, “Estimation of wind energy potential using different probability density functions”, Applied Energy, Vol. 88, pp. 1848–1856, 2011.
• M. Nedaei. “Wind Energy Potential Assessment in Chalus County in Iran”, Int. J. Renewable Energy Research, Vol. 2, No. 2, pp. 338–347, 2012. [13] S. Rehman, N.M. Al–Abbadi, “Wind shear coefŞcient, turbulence intensity and wind power potential assessment for Dhulom, Saudi Arabia”, Renewable Energy, Vol. 33, pp. 2653–2660, 2008. [14] A.A. Bhuiyan, A.K.M.S. Islam, A.I. Alam. “Application of Wind Resource Assessment (WEA) Tool: A case study in Kuakata, Bangladesh”, Int. J. Renewable Energy Research, Vol. 1, No. 3, pp. 192– 199, 2011.
• G. Gualtieri, “Development and Application of an Integrated Wind Resource Assessment Tool for Wind Farm Planning”, Int. J. Renewable Energy Research, Vol. 2, No. 4, pp. 674–685, 2012.
• D.A. Spera, Wind Turbine Technology: Fundamental Concepts of Wind Turbine Engineering, 2nd ed. New York: ASME Press, 2009.
• S. Rehman, L.M. Al–Hadhrami, M.M. Alam, J.P. Meyer, “Empirical correlation between hub height and local wind shear exponent for different sizes of wind turbines”, Sustainable Energy Technologies and Assessments, Vol. 4, pp. 45–51, 2013.
• J. Counihan, “Adiabatic Atmospheric Boundary Layers: A Review and Analysis of Data Collected from the Period 1880–1972”, Atmos. Env., Vol. 9, pp. 871–905, 1975.
• J.S. Irwin, “A theoretical variation of the wind profile power law exponent as a function of surface roughness length and stability”, Atmos. Env., Vol. 13, pp. 191–194, 1979.
• Ž. Ðurisic, J. Mikulovic, “A model for vertical wind speed data extrapolation for improving wind resource assessment using WasP”, Renewable Energy, Vol. 41, pp. 407–411, 2012.
• G. Gualtieri, S. Secci, “Extrapolating wind speed time series vs. Weibull distribution to assess wind resource to the turbine hub height: A case study on coastal location in Southern Italy”, Renewable Energy, Vol. 62, pp. 164–176, 2014.
• G.P. Van den Berg, “Wind turbine power and sound in relation to atmospheric stability”, Wind Energy, Vol. 11, pp. 151–169, 2008.
• M.L. Kubik, P.J. Coker, J.F. Barlow, C. Hunt, “A study into the accuracy of using meteorological wind data to estimate turbine generation output”, Renewable Energy, Vol. 51, pp. 153–158, 2013.
• J.D. Pneumatikos, “An experimental test of the empirical formulae commonly used to represent wind speed profiles near the ground”, Renewable Energy, Vol. 1, Nos. 5/6, pp. 623–628, 1991.
• S.T. Frandsen, Turbulence and turbulence generated fatigue in wind turbine clusters, Report R–1188, Risİ National Laboratory, Roskilde, Denmark, 2007. [26] M.C.H.
• Hui, A. Larsen, H.F. Xiang, “Wind
• turbulence characteristics study at the Stonecutters
• Bridge site: Part I–Mean wind and turbulence
• intensities”, J Wind Eng Ind Aerodyn, Vol. 97, pp. 22– 36, 2009.
• G. Gualtieri, G. Zappitelli, “Investigating wind resource, turbulence intensity and gust factor on mountain locations in Southern Italy”, Int. J. of Green Energy, Vol. 12, No. 5, pp. 309–327, 2015.
• H. Ishizaki, “Wind profiles, turbulence intensities and gust factors for design in Typhoon–prone regions”, J Wind Eng Ind Aerodyn, Vol. 13, pp. 55–66, 1983.
• J.W. Verkaik, A.A.M. Holtslag, “Wind profiles, momentum fluxes and roughness lengths at Cabauw revisited”, Boundary–Layer Meteorol, Vol. 122, pp. 701–719, 2007.
• N.M. Al–Abbadi, S. Rehman, “Wind speed and wind power characteristics for Gassim, Saudi Arabia”, Int. J. Green Energy, Vol. 6, pp. 201–217, 2009.
• Enercon wind turbines, E–33 technical specifications, http://www.enercon.de/p/downloads/EN_Productover view_0710.pdf, 2014.
• AWE wind turbines, 52–750 technical specifications, available at: http://www.awewind.com, 2014. [33] Gamesa wind turbines, G58–850 technical specifications, http://www.gamesacorp.com, 2014. available at: [34] Vestas wind turbines, V90–2.0 technical specifications, available at: http://www.vestas.com, 2014. [35] Suzlon wind turbines, S88–2.1 technical specifications, available at: http://www.suzlon.com,
• Nordex wind turbines, N100 technical specifications, available at: http://www.nordex–online.com, 2014.