Evaluation of the Power-Law Wind-Speed Extrapolation Method with Atmospheric Stability Classification Methods for Flows over Different Terrain Types

Abstract

The atmospheric stability and ground topography play an important role in shaping wind-speed profiles. However, the commonly used power-law wind-speed extrapolation method is usually applied, ignoring atmospheric stability effects. In the present work, a new power-law wind-speed extrapolation method based on atmospheric stability classification is proposed and evaluated for flows over different types of terrain. The method uses the wind shear exponent estimated in different stability conditions rather than its average value in all stability conditions. Four stability classification methods, namely the Richardson Gradient (RG) method, the Wind Direction Standard Deviation (WDSD) method, the Wind Speed Ratio (WSR) method and the Monin–Obukhov (MO) method are applied in the wind speed extrapolation method for three different types of terrain. Tapplicability is analyzed by comparing the errors between the measured data and the calculated results at the hub height. It is indicated that the WSR classification method is effective for all the terrains investigated while the WDSD method is more suitable in plain areas. Moreover, the RG and MO methods perform better in complex terrains than the other methods, if two-level temperature data are available.

Advancing Wind Resource Assessment in Complex Terrain with Scanning Lidar Measurements

“…Although 0.2 shear exponent is higher than the classical 1/7 shear exponent for neutral conditions, it is more reasonable in this case since we have a complex terrain with heterogeneous forest. This topic has been discussed in an early technical note [28] and more recently in [29]. In both articles, researchers showed the variation in shear exponent based on measurements with respect to terrain complexity and stability.…”

Special Issue on Wind Turbine Aerodynamics

“…Ehrich et al [4] compared the blade element momentum theory, actuator line method, and computational fluid dynamics in the case of a wind turbine under turbulence inflow by checking its sectional and integral forces in terms of mean, standard deviation, power spectral density and fatigue loads. As wind flow measurements are often carried out at low heights, Xu et al [5] evaluated the power-law wind-speed extrapolation method for flows over different terrain types and a new wind-speed extrapolation method based on atmospheric stability classification methods was developed. Schaffarczyk and Jeromin [6] analyzed the measured high-frequency atmospheric turbulence and its impact on the boundary layer of wind turbine blades, and found that the stability state in the atmospheric boundary does not seem to depend on simple properties, but on higher statistical properties, such as shape factors.…”

The role of the power law exponent in wind energy assessment: A global analysis

“…Another approach to calculate spatiotemporal explicit E values is to use U measurements from a tower equipped with U measurement sensors. 27 It is usually not possible to realize such measurements, due to logistical and financial reasons.…”

“…For instance, using a Light Detection and Ranging (LIDAR) system, long‐term U observations were obtained in Singapore 25 and Ohio (USA) 26 to calculate spatiotemporal explicit E values. Another approach to calculate spatiotemporal explicit E values is to use U measurements from a tower equipped with U measurement sensors 27 . It is usually not possible to realize such measurements, due to logistical and financial reasons.…”