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Arnab Sarkar,Sneh Deep,D. Datta,Amit Vijaywargiya,R. Roy,V. S. Phanikanth 대한토목학회 2019 KSCE Journal of Civil Engineering Vol.23 No.8
Wind velocity data modeling plays a crucial role for the estimation of wind load and wind energy. Apart from these, the same modeling must also be used in the load cycle analysis of fatigue failure in slender structures to address periodic vortex shedding. Most authors fitted the entire available range of wind velocities of various locations using Weibull models. However, they did not check the validity of the model in describing the range of extreme wind velocity. In this work, the validity of Weibull models for describing parent as well as extreme hourly mean wind velocity data for four places on the east coast of India has been checked. While it predicts lower wind speeds accurately, the Weibull model has been found to become inappropriate for describing wind velocity in the range of extremes, i.e., above a certain threshold value. Therefore, this article focuses on the techniques of determininga limiting wind velocity beyond which the Weibull distribution is rendered unsuitable. In the range where the Weibull distributionfails, various extreme value distributions, such as Gumbel, Fréchet and reverse Weibull distributions have been compared, therebydetermining the best estimator for each location.
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Weibull Model for Wind Speed Data Analysis of Different Locations in India
Arnab Sarkar,Gaurav Gugliani,Sneh Deep 대한토목학회 2017 KSCE JOURNAL OF CIVIL ENGINEERING Vol.21 No.7
Wind speed data should be fitted by a suitable statistical model like Weibull to determine expected number of hours per year in the critical wind speed range for a slender structure, which is required to determine the expected number of stress cycles in the projected working life of the structure. Apart from this, for the assessment of wind energy potential wind speed data should be fitted by an appropriate probability distribution. In the present scope of study, wind data of various locations of India have been fitted by Weibull model. Wind speed data are initially sampled in knot by Indian Meteorological Department and later converted into integer km/h before supplying them to the end user. Due to this conversion, wind speed data cannot be properly fitted by Weibull distribution and in this regard, the choice of appropriate class width becomes very much important. Without the choice of appropriate class width, estimated Weibull parameters become biased which would yield incorrect estimation of expected number of hours in critical wind speed ranges as well as wind energy potential. After taking appropriate class width of 4 km/h, it has been found that Weibull model is an adequate model to describe wind speed distributions of India. Weibull model has also been compared with other models such as Gamma and inverse Weibull distributions to establish its suitability than the others. In this study, the values of Weibull shape parameters vary from 1.3 to 2.3, whereas the values of scale parameters vary from 1.4 m/s to 6.5 m/s. The validity of Weibull model is also verified with a target confidence interval of 90%. The uncertainties involved in the estimation of available wind energy potential as well as the expected number of hours per year in critical wind speed ranges have also been considered due to random variation of wind climate in each year.
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