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In this study, the coefficients of Weibull Distribution Function (WDF) were calculated at two different heights using by six different methods. One-year wind data were used to determine the coefficients of WDF at different heights, and the wind data were obtained from a metrology station with a height of 10 m and a real wind turbine with a height of 80 m in Turkey's Hatay region. The used methods in this study were Graphical Method (GM), Empirical Method, Energy Pattern Method (EPM), Energy Trend Method, Maximum Likelihood Method and Moment Method.\ Three different statistical error analysis tests were used to compare the performance of the used methods at two different heights. Estimated mean wind speed and power values are the most important indicators to evaluate the performance of the used methods. In this study, mean wind speeds and powers were estimated in all methods for both heights using the WDF. These obtained values were compared with the actual real data and the best performing method was determined at both different heights for selected region. When the results were evaluated in general at both different heights, it was seen that the best performance method was the EPM and the worst performance method was the GM. [ABSTRACT FROM AUTHOR]

The use of wind as an energy source is becoming popular because of its non-polluting and renewable features. There is an urgent request to develop site-based estimation on wind engineering, which can be used for optimal design of wind turbines and wind farming. The wind speed for Zafarana Project in Suez Gulf, namely Site-3, based on monthly averaged data for 1 year as well as every 10 min for two days, one day in summer season and one day one winter season have been analyzed to estimate the most appropriate method to find Weibull distribution parameters for this site. The investigated methods are the mean wind speed method, the maximum likelihood method, the modified maximum likelihood method, the graphical method and the power density method. These methods results have been compared with the provided data to find their accuracy based on the root mean square errors. From the obtained results, the mean wind speed and the maximum likelihood method are recommended in estimating the wind speed distribution for the studied site in Zafarana wind farm. [ABSTRACT FROM AUTHOR]