LAUSR

Abstract With growing wind turbine sizes and increasing demands for electricity, it is important to determine accurately wind shear profile, up to high altitudes, for large scale wind turbine installation. The installed wind turbine towers in Iran have hardly exceeded the height of 40 m. In this study, the effectiveness of different extrapolation methods are investigated to determine robustly wind speed and wind power density at higher altitudes. As a case study, wind data was collected from the center of Iran which consists of 35 wind stations in nine provinces. For precise evaluation, the wind speed data were recorded based on 10-min average at various heights ranging from 10 m to 100 m and the wind power potential was obtained on both seasonally and daily basis. The widely used Weibull distribution function is selected for which the shape factor and scale parameter are determined using the standard deviation method, the empirical method of Lysen and the power density method at different heights. From the extrapolated wind data, the mean wind speed, wind power density, optimal wind speed, probability and cumulative density distributions are obtained and the geographic information systems maps are produced and discussed. The results indicate that the power density method is the most accurate method for extrapolating wind characteristics. From the results, it is also observed that variation of power density with time is significant. In period I (spring and summer), most parts of the center of Iran have significant potential for installing large scale wind turbines. However in period II (fall and winter), the amount of wind power density decreases considerably. In overall, the north western and north eastern parts of the center of Iran are recommended for large scale wind turbine installation. The methodology discussed here can be equally employed for extrapolating of wind speeds data at any heights within any geographical region.