Abstract
Abstract. The objective of this paper is to compare field data from a scanning lidar mounted on a turbine to control-oriented wind turbine wake models. The measurements were taken from the turbine nacelle looking downstream at the turbine wake. This field campaign was used to validate control-oriented tools used for wind plant control and optimization. The National Wind Technology Center in Golden, CO, conducted a demonstration of wake steering on a utility-scale turbine. In this campaign, the turbine was operated at various yaw misalignment set points, while a lidar mounted on the nacelle scanned five downstream distances. Primarily, this paper examines measurements taken at 2.35 diameters downstream of the turbine. The lidar measurements were combined with turbine data and measurements of the inflow made by a highly instrumented meteorological mast on-site. This paper presents a quantitative analysis of the lidar data compared to the control-oriented wake models used under different atmospheric conditions and turbine operation. These results show that good agreement is obtained between the lidar data and the models under these different conditions.
Highlights
Wind plant control can be used to maximize the power production of a wind plant, reduce structural loads to increase the lifetime of turbines in a wind plant, and better integrate wind energy into the energy market (Johnson and Thomas, 2009; Boersma et al, 2017)
The results presented show the comparison between the wake models described in Sect. 2 and the lidar data collected in the field campaign described Sect
The results focus on comparisons of the velocity deficit behind the turbine, the wake deflection achieved in yaw misalignment conditions, and varying atmospheric conditions
Summary
Wind plant control can be used to maximize the power production of a wind plant, reduce structural loads to increase the lifetime of turbines in a wind plant, and better integrate wind energy into the energy market (Johnson and Thomas, 2009; Boersma et al, 2017). There has been a significant amount work done on wake steering, showing that this method has the most potential to increase power production (Annoni et al, 2015; Gebraad et al, 2016). Various computational fluid dynamics simulations and wind tunnel experiments have shown that this method can increase power without substantially increasing turbine loads (Gebraad et al, 2016; Fleming et al, 2014; Jiménez et al, 2010). Yaw-based wake steering control has been used in optimization studies of turbine layouts to improve the annual energy production of a wind plant (Fleming et al, 2016; Thomas et al, 2015; Stanley et al, 2017). Recent computational fluid dynamics (CFD) studies have determined that the shape of the wake and atmospheric stability are significant factors in wake steering (Vollmer et al, 2016)
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