Abstract
To study the wake development characteristics of wind farms in complex terrains, two different types of Light Detection and Ranging (LiDAR) were used to conduct the field measurements in a mountain wind farm in Hebei Province, China. Under two different incoming wake conditions, the influence of wind shear, terrain and incoming wind characteristics on the development trend of wake was analyzed. The results showed that the existence of wind shear effect causes asymmetric distribution of wind speed in the wake region. The relief of the terrain behind the turbine indicated a subsidence of the wake centerline, which had a linear relationship with the topography altitudes. The wake recovery rates were calculated, which comprehensively validated the conclusion that the wake recovery rate is determined by both the incoming wind turbulence intensity in the wake and the magnitude of the wind speed.
Highlights
The upstream wind turbines are driven by the incoming wind, which reduce the downstream wind speed and increase the turbulence intensity, and the wakes of upstream wind turbines affect the downstream wind turbines
This study aims to analyze the wake distribution characteristics of a single wind turbine under different inflow wind conditions in complex terrain, which will be beneficial to the layout optimization of wind farms and the yaw control of wind turbines
The Plan-Position-Indicator mode (PPI) mode mainly measures the distribution of wind speed on the horizontal plane by changing the azimuth at a fixed elevation angle, while the Range-Height-Indicator mode (RHI) mode measures the distribution of wind velocity on the vertical plane by varying the elevation angle and fixing the azimuth angle [33,34]
Summary
The upstream wind turbines are driven by the incoming wind, which reduce the downstream wind speed and increase the turbulence intensity, and the wakes of upstream wind turbines affect the downstream wind turbines. It can be concluded that previous research work mainly focused on wake interaction of multiple turbines and wake flow field distribution in wind farms with complex terrain, but the influence of incoming wind characteristics and topography on the wake development characteristics of a single wind turbine is not further quantified. In this instance, the Doppler-Beam-Swing mode (DBS) of WP350 and the Range-Height-Indicator mode (RHI) of 3D6000 are used in this study to obtain the incoming wind data and wake data of a 1.5 MW wind turbine under a complex terrain.
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