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Statistical tests for the distribution of surface wind and current speeds across the globe

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  • Campisi-Pinto, Salvatore
  • Gianchandani, Kaushal
  • Ashkenazy, Yosef

Abstract

The distribution of surface winds and currents is important from climatic and energy production aspects. It is commonly assumed that the distribution of surface winds and currents speed is Weibull, yet, previous studies indicated that this assumption is not always valid. An inaccurate probability distribution function (PDF) of wind (current) statistic can lead to erroneous power estimation; thus, it is necessary to examine the accuracy of the PDFs employed. We propose statistical tests to check the validity of an assumed distribution of wind and current speeds. The main statistical test can be applied to any distribution and is based on surrogate data where the different moments of the data are compared with the moments of the surrogate data. We applied this and other tests to global surface wind and current speeds and found that the generalized gamma distribution fits the data distributions better than the Weibull distribution. The percentage of locations that fall within the confidence interval of the assumed distribution varies with the moment. The third moment is used to estimate the potential power of winds and currents — we find that 89% (95%) of the wind (current) grid points fall within the 95% confidence interval of the generalized gamma distribution.

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  • Campisi-Pinto, Salvatore & Gianchandani, Kaushal & Ashkenazy, Yosef, 2020. "Statistical tests for the distribution of surface wind and current speeds across the globe," Renewable Energy, Elsevier, vol. 149(C), pages 861-876.
    • Handle: RePEc:eee:renene:v:149:y:2020:i:c:p:861-876
    DOI: 10.1016/j.renene.2019.12.041
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