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.

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Abstract.Wind turbines in a wind farm operate individually to maximize their own performance regardless of the impact of aerodynamic interactions on neighboring turbines. Wind farm controls can be used to increase power production or reduce overall structural loads by properly coordinating turbines. One wind farm control strategy that is addressed in literature is known as wake steering, wherein upstream turbines operate in yaw misaligned conditions to redirect their wakes away from downstream 5 turbines. The National Renewable Energy Laboratory (NREL) in Golden, CO conducted a demonstration of wake steering on a single utility-scale turbine. In this campaign, the turbine was operated at various yaw misalignment setpoints while a lidar mounted on the nacelle scanned five downstream distances. The lidar measurements were combined with turbine data, as well as measurements of the inflow made by a highly instrumented meteorological mast upstream. The full-scale measurements are used to validate controls-oriented tools, including wind turbine wake models, used for wind farm controls and optimization. 10This paper presents a quantitative comparison of the lidar data and controls-oriented wake models under different atmospheric conditions and turbine operation. The results show good agreement between the lidar data and the models under these different conditions.

Abstract. Renewed interest in yaw control for wind turbine and power plants for wake redirection and load mitigation demands a clear understanding of the effects of running with skewed inflow. In this paper, we investigate the physics of yawed operations, building up the complexity from a simplified analytical treatment to more complex aeroelastic simulations. Results in terms of damage equivalent loads (DELs) and extreme loads under misaligned conditions of operation are compared to data collected from an instrumented, utility-scale wind turbine. The analysis shows that multiple factors are responsible for the DELs of the various components and that airfoil aerodynamics, elastic characteristics of the rotor, and turbulence intensities are the primary drivers. Both fatigue and extreme loads are observed to have relatively complex trends with yaw offsets, which can change depending on the wind-speed regime. Good agreement is found between predicted and measured trends for both fatigue and ultimate loads.

Abstract. Renewed interest in yaw control for wind turbine and power plants for wake redirection and load mitigation demands a clear understanding of the effects of running with skewed inflow. In this paper, we investigate the physics of yawed operations, building up the complexity from a simplified analytical treatment to more complex aeroelastic simulations. Results in terms of damage equivalent loads (DELs) and extreme loads under operating, misaligned conditions are compared to data collected from an instrumented, utility-scale wind turbine. The analysis shows that multiple factors are responsible for the DELs of 5 the various components, and that airfoil aerodynamics, elastic characteristics of the rotor, and turbulence intensities are the primary drivers. Both fatigue and extreme loads are observed to have relatively complex trends with yaw offsets, which can change depending on the wind-speed regime. Good agreement is found between predicted and measured trends for both fatigue and ultimate loads.