Abstract. Wake steering is a form of wind farm control in which turbines use
yaw offsets to affect wakes in order to yield an increase in total energy
production. In this first phase of a study of wake steering at a commercial
wind farm, two turbines implement a schedule of offsets. Results exploring
the observed performance of wake steering are presented and some
first lessons learned. For two closely spaced turbines, an approximate
14 % increase in energy was measured on the downstream turbine over a
10∘ sector, with a 4 % increase in energy production of the
combined upstream–downstream turbine pair. Finally, the influence of
atmospheric stability over the results is explored.
Abstract. Wake steering is a form of wind farm control in which turbines use yaw offsets to affect wakes in order to yield an increase in total energy production. In this first phase of a study of wake steering at a commercial wind farm, two turbines implement a schedule of offsets. Results exploring the observed performance of wake steering are presented, as well as some first lessons learned. For two closely spaced turbines, an approximate 13 % increase in energy was measured on the downstream turbine over a 10° sector. Additionally, the increase of energy for the combined upstream/downstream pair was found to be in line with prior predictions. Finally, the influence of atmospheric stability over the results is explored.
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.
Abstract. This paper presents the results of a field campaign investigating the performance of wake steering applied at a section of a commercial wind farm. It is the second phase of the study for which the first phase was reported in Fleming et al. (2019). The authors implemented wake steering on two turbine pairs, and compared results with the latest FLORIS (FLOw Redirection and Induction in Steady State) model of wake steering, showing good agreement in overall energy increase. Further, although not the original intention of the study, we also used the results to detect the secondary steering phenomenon. Results show an overall reduction in wake losses of approximately 6.6 % for the regions of operation, which corresponds to achieving roughly half of the static optimal result.
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.
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