Assessment of wind energy resources in the urat area using optimized weibull distribution

Abstract

Accurate assessment and analysis of wind energy resources are the key to wind farm planning. In this study, we evaluate the wind energy resource potential in the Urat area of Inner Mongolia, China, based on data measured from four 70–100 m/s wind tower. We first model the wind speed by the Weibull distribution where the parameters are estimated by various numerical and intelligent optimization methods. In particular, we introduce the Cross Entropy Method (CEM) and find that it outperforms other methods. Based on the Weibull model, we then evaluate six wind energy metrics for the Urat area. It is shown that the annual average wind speed and wind power density are up to 9.33 m/s and 941 W/m2, respectively, with over 7000 h of annual available time. The wind is relative stable for all seasons except for a mild reduction in speed and a change of direction in summer. The low power production cost and rapid payback period make the Urat area a promising location for deploying wind farms.