Remote Sensing, Vol. 12, Pages 1091: Improving VerticalWind Speed Extrapolation Using Short-Term Lidar Measurements (Remote Sensing)

This study investigates how short-term lidar measurements can be used in combinationwith a mast measurement to improve vertical extrapolation of wind speed. Several methods aredeveloped and analyzed for their performance in estimating the mean wind speed, the windspeed distribution, and the energy yield of an idealized wind turbine at the target height ofthe extrapolation. These methods range from directly using the wind shear of the short-termmeasurement to a classification approach based on commonly available environmental parametersusing linear regression. The extrapolation strategies are assessed using data of ten wind profiles upto 200 m measured at different sites in Germany. Different mast heights and extrapolation distancesare investigated. The results show that, using an appropriate extrapolation strategy, even a veryshort-term lidar measurement can significantly reduce the uncertainty in the vertical extrapolation ofwind speed. This observation was made for short as well as for very large extrapolation distances.Among the investigated methods, the linear regression approach yielded better results than the othermethods. Integrating environmental variables into the extrapolation procedure further increased theperformance of the linear regression approach. Overall, the extrapolation error in (theoretical) energyyield was decreased by around 50% to 70% on average for a lidar measurement of approximately oneto two months depending on the extrapolation height and distance. The analysis of seasonal patternsrevealed that appropriate extrapolation strategies can also significantly reduce the seasonal bias thatis connected to the season during which the short-term measurement is performed.