Open AccessWind LiDAR Measurements of Wind Turbine Wakes Evolving over Flat and Complex Terrains: Ensemble Statistics of the Velocity Field
Author(s) -
Lu Zhan,
Stefano Letizia,
Giacomo Valerio Iungo
Publication year - 2020
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1452/1/012077
Subject(s) - lidar , wake , wind speed , wind shear , anemometer , orography , terrain , meteorology , wind profile power law , maximum sustained wind , environmental science , log wind profile , wind gradient , turbine , geology , wind direction , wind power , remote sensing , precipitation , geography , physics , aerospace engineering , mechanics , engineering , cartography , electrical engineering
Wind velocity measurements of wakes generated by utility-scale wind turbines were performed with the University of Texas at Dallas (UTD) mobile LiDAR station for wind farms in flat and complex terrains. Single-wake LiDAR measurements are clustered according to incoming wind speed at hub height and atmospheric stability regime through the wind shear exponent. Ensemble statistics of the LiDAR data shows that the velocity field in the near-wake is mainly affected by the rotor thrust coefficient, while atmospheric stability is the prevailing factor governing wake recovery. For the wind farm in complex terrain, the wind field is significantly affected by the local orography, showing either local speed-up or low-velocity regions. The analysis of the SCADA data corroborates the occurrence of these wind features and enables quantifying their effects on the wind plant performance.