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Heterogeneous mixture distributions for modeling wind speed, application to the UAE

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  • Shin, Ju-Young
  • Ouarda, Taha B.M.J.
  • Lee, Taesam

Abstract

Heterogeneous mixture distributions (HTM) have not been employed for wind speed modeling of the Arabian Peninsula. In order to improve our understanding of wind energy potential in the Arabian Peninsula, HTM should be tested for the frequency analysis of wind speed. The aim of the current study is to assess the suitability of HTMs and identify the most appropriate probability distribution to model wind speed data in the UAE. Hourly mean wind speed data were used in the current study. Ten homogeneous and heterogeneous mixture distributions were used and constructed by mixing the four following probability distributions: Gamma, Weibull, Extreme value type-one, and Normal distributions. The Weibull and Kappa distributions were also employed as representatives of the conventional non-mixture distributions. Maximum Likelihood, Expectation Maximization algorithm, and Least Squares methods were employed to fit the mixture distributions. Results indicate that mixture distributions give the best fit to wind speed data for all stations. Wind speed data of five stations show strong mixture distributional characteristics. Applications of HTMs show a significant improvement in explaining the whole wind speed regime. The Weibull-Extreme value type-one mixture distribution is considered the most appropriate distribution for wind speed data in the UAE.

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  • Shin, Ju-Young & Ouarda, Taha B.M.J. & Lee, Taesam, 2016. "Heterogeneous mixture distributions for modeling wind speed, application to the UAE," Renewable Energy, Elsevier, vol. 91(C), pages 40-52.
    • Handle: RePEc:eee:renene:v:91:y:2016:i:c:p:40-52
    DOI: 10.1016/j.renene.2016.01.041
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