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A model for vertical wind speed data extrapolation for improving wind resource assessment using WAsP

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  • Đurišić, Željko
  • Mikulović, Jovan

Abstract

A mathematical model for vertical extrapolation of the measurement data for wind speed taken at several measurement heights is presented. The model is based on the method of least squares (LES). By applying the proposed model on the sets of measured data taken at least at three measurement heights, one obtains a synthetic set of data at a desired height where the wind power potential is analyzed. The basic idea is that during the process of estimation of the wind power potential the measurement data are first extrapolated by the proposed method and then by using program WAsP the spatial extrapolation is carried out. The algorithm is tested by one year wind speed measurement data taken at three locations characterized by different topographies of the terrain and different climatic conditions. The performed analyses show that pre-processing of measurement data by the proposed method results in a better estimate of the wind power potential at a height which is greater than the measurement heights compared to that obtained by the standard application of WAsP program which makes use of measurement data taken at one measurement height.

Suggested Citation

  • Đurišić, Željko & Mikulović, Jovan, 2012. "A model for vertical wind speed data extrapolation for improving wind resource assessment using WAsP," Renewable Energy, Elsevier, vol. 41(C), pages 407-411.
    • Handle: RePEc:eee:renene:v:41:y:2012:i:c:p:407-411
    DOI: 10.1016/j.renene.2011.11.016
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    Cited by:

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    3. Li, Jiale & Wang, Xuefei & Yu, Xiong (Bill), 2018. "Use of spatio-temporal calibrated wind shear model to improve accuracy of wind resource assessment," Applied Energy, Elsevier, vol. 213(C), pages 469-485.
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    8. Bahamonde, Manuel Ignacio & Litrán, Salvador P., 2019. "Study of the energy production of a wind turbine in the open sea considering the continuous variations of the atmospheric stability and the sea surface roughness," Renewable Energy, Elsevier, vol. 135(C), pages 163-175.
    9. Gualtieri, Giovanni, 2019. "A comprehensive review on wind resource extrapolation models applied in wind energy," Renewable and Sustainable Energy Reviews, Elsevier, vol. 102(C), pages 215-233.
    10. Murthy, K.S.R. & Rahi, O.P., 2017. "A comprehensive review of wind resource assessment," Renewable and Sustainable Energy Reviews, Elsevier, vol. 72(C), pages 1320-1342.
    11. Chandel, S.S. & Ramasamy, P. & Murthy, K.S.R, 2014. "Wind power potential assessment of 12 locations in western Himalayan region of India," Renewable and Sustainable Energy Reviews, Elsevier, vol. 39(C), pages 530-545.
    12. Wang, Qiang & Luo, Kun & Yuan, Renyu & Zhang, Sanxia & Fan, Jianren, 2019. "Wake and performance interference between adjacent wind farms: Case study of Xinjiang in China by means of mesoscale simulations," Energy, Elsevier, vol. 166(C), pages 1168-1180.

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