Field test of wake steering at an offshore wind farm

Fleming, Paul; Annoni, Jennifer; Shah, Jigar; Wang, Linpeng; Ananthan, Shreyas; Zhang, Zhijun; Hutchings, Kyle; Wang, Peng; Chen, Weiguo; Chen, Lin

doi:10.5194/wes-2-229-2017

Cited by 254 publications

(233 citation statements)

References 19 publications

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“…Fleming et al, 2014b;Gebraad et al, 2014) and in a field test in a full-scale wind farm (Fleming et al, 2017), showing promising results as the total power yield could be increased in the mentioned studies.…”

mentioning

confidence: 82%

Wind tunnel experiments on wind turbine wakes in yaw: Redefining the wake width

Schottler¹,

Bartl²,

Mühle³

et al. 2018

Preprint

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Abstract. This paper presents an investigation of wakes behind model wind turbines, including cases of yaw misalignment. Two different turbines were used and their wakes are compared, isolating effects of boundary conditions and turbine specifications. The results show that areas of strongly heavy-tailed distributed velocity increments are surrounding the velocity deficit in all cases examined. Thus, a wake is significantly wider when two-point statistics are included as opposed to a description limited to one-point quantities. As non-Gaussian distributions of velocity increments affect loads of downstream rotors, our findings impact the application of active wake steering through yaw misalignment as well as wind farm layout optimizations and should 10 therefore be considered in future wake studies, wind farm layout and farm control approaches. Further, the velocity deficits behind both turbines are deformed to a kidney-like curled shape during yaw misalignment, for which parameterization methods are introduced. Moreover, the lateral wake deflection during yaw misalignment is investigated.

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mentioning

confidence: 82%

Wind tunnel experiments on wind turbine wakes in yaw: Redefining the wake width

Schottler¹,

Bartl²,

Mühle³

et al. 2018

Preprint

View full text Add to dashboard Cite

show abstract

“…Figure 5 shows the wake deflection under turbine yaw misalignment observed by the scanning lidar at 2.35D downstream. Under larger yaw angles, the wake deflects and deforms as reported in (Howland et al (2016);Fleming et al (2017c)). Again, the Gaussian model is better able to predict the conditions at no misalignment (predicts velocities within the confidence intervals) since the multi-zone and Jensen model were both tuned to data with a lower turbulence intensity.…”

mentioning

confidence: 85%

“…Wind tunnel tests have been conducted that show encouraging results that match simulation results based on wake redirection (Campagnolo et al (2016); Schottler et al (2016)). In addition, there are preliminary results of the benefits of wake steering from an offshore commercial wind farm (Fleming et al (2017c)). NREL also conducted a detailed full- 15 scale demonstration in which a utility-scale turbine was operated at various yaw offsets while the wake was measured using a scanning lidar.…”

Section: Introductionmentioning

confidence: 99%

Analysis of Control-Oriented Wake Modeling Tools Using Lidar Field Results

Annoni¹,

Fleming²,

Scholbrock³

et al. 2018

Preprint

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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.

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“…In this model, the wake appears as a deficit of energy that flows downstream and is characterized as (i) an initial deficit determined by the turbine thrust, (ii) a rate of recovery determined by topology (i.e., FLORIS inherits wake-recovery parameters from the Jensen model whose values are set by rules of thumb for onshore or offshore), and (iii) a wake deflection caused by wake steering. This version of FLORIS was used to design a strategy for wake steering that was tested at a commercial offshore wind farm in Fleming et al (2017b), with an improved wind farm power performance under waked conditions.…”

Section: Introductionmentioning

confidence: 99%

A simulation study demonstrating the importance of large-scale trailing vortices in wake steering

et al. 2018

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Abstract. In this paper, we investigate the role of flow structures generated in wind farm control through yaw misalignment. A pair of counter-rotating vortices is shown to be important in deforming the shape of the wake and in explaining the asymmetry of wake steering in oppositely signed yaw angles. We also demonstrate that vortices generated by an upstream turbine that is performing wake steering can deflect wakes of downstream turbines, even if they are themselves aligned.We encourage the development of improvements to control-oriented engineering models of wind farm control, to include the effects of these large-scale flow structures. Such a new model would improve the predictability of control-oriented models. Further, we demonstrate that the vortex structures created in wake steering can lead to greater impact on power generation than currently modeled in control-oriented models. We propose that wind farm controllers can be made more effective if designed to take advantage of these effects.

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Field test of wake steering at an offshore wind farm

Cited by 254 publications

References 19 publications

Wind tunnel experiments on wind turbine wakes in yaw: Redefining the wake width

Wind tunnel experiments on wind turbine wakes in yaw: Redefining the wake width

Analysis of Control-Oriented Wake Modeling Tools Using Lidar Field Results

A simulation study demonstrating the importance of large-scale trailing vortices in wake steering

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