N. Vivekanandan
Extreme Value Analysis (EVA) of wind speed plays an important role in estimating the design values of the wind load-effect on structures for any structural design. This can be carried out by fitting of probability distributions to the series of Annul Maximum Wind Speed (AMWS) data. This paper illustrates the adoption of Gumbel (EV1), Frechet (EV2), 2-parameter Log Normal (LN2) and Log Pearson Type-3 (LP3) distributions for estimation of Extreme Wind Speed (EWS) using AMWS recorded at Delhi. For determination of parameters of EV1, EV2, LN2 and LP3 distributions, Method of Moments (MoM) and Maximum Likelihood Method (MLM) are used. In addition to MoM and MLM, method of least squares and Order Statistics Approach (OSA) are also used for determination of parameters of EV1 and EV2 distributions. Goodness-of-Fit (GoF) tests viz., Anderson-Darling and Kolmogorov-Smirnov are applied for checking the adequacy of fitting of probability distributions to the recorded data. Diagnostic test (D-index) is used for the selection of suitable probability distribution for EVA of wind speed. Based on GoF and diagnostic test results, the study suggests the EV1 (OSA) is better suited probability distribution for estimation of EWS for Delhi.
Anderson-Darling, D-index, Kolmogorov-Smirnov, Probability Distribution, Wind Speed