Comparison of Estimators of Extreme Value Distributions for Wind Data Analysis

Journal Title: Bonfring International Journal of Data Mining - Year 2012, Vol 2, Issue 3

Abstract

Estimation of extreme wind speed potential at a region is of importance while designing tall structures such as cooling towers, stacks, transmission line towers, etc. Assessment of wind speed can expediently be carried out by probabilistic modelling of historic wind speed data using extreme value distribution, or by using standard procedures available under BIS code of practices for building and structures. This paper illustrates the use of extreme value distributions such as Gumbel, Frechet and Weibull for modelling wind speed data recorded at Kanyakumari. Method of Least Squares (MLS), maximum likelihood method and order statistics approach are used for determination of parameters of the distributions. Kolmogorov-Smirnov test is used for checking the adequacy of fitting the method/ distribution to the recorded data. D-index is used for selection of suitable method/ distribution for estimation of design wind speed. The study shows that the Gumbel distribution using MLS is better suited for estimation of design wind speed for Kanyakumari. A comparative study of wind speed estimates obtained using MLS of Gumbel and with BIS code of practices is carried out; and results presented.

Authors and Affiliations

Vivekanandan N

Keywords

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  • EP ID EP103837
  • DOI 10.9756/BIJDM.1503
  • Views 153
  • Downloads 0

How To Cite

Vivekanandan N (2012). Comparison of Estimators of Extreme Value Distributions for Wind Data Analysis. Bonfring International Journal of Data Mining, 2(3), 16-20. https://europub.co.uk./articles/-A-103837