Field Test of Wake Steering at an Offshore Wind Farm

Abstract

Abstract. In this paper, a field test of wake steering control is presented. The field test is the result of a collaboration between the National Renewable Energy Laboratory (NREL) and Envision Energy, a smart energy management company and turbine manufacturer. In the campaign, an array of turbines within an operating commercial offshore wind farm in China have the normal yaw controller modified to implement wake steering according to a yaw control strategy. The strategy was designed using NREL wind farm models, including a computational fluid dynamics model, SOWFA, for understanding wake dynamics and an engineering model, FLORIS, for yaw control optimization. Results indicate that, within the certainty afforded by the data, the wake-steering controller was successful in increasing power capture, by amounts similar to those predicted from the models.

Influence of atmospheric conditions on the power production of utility-scale wind turbines in yaw misalignment

“…Schreiber et al (2017) 19 and Draper et al (2018) 20 used wind tunnel experiments and LES to show that P p ≈ 1.8 for a wind turbine in sheared freestream conditions. Fleming et al (2017) 6 found P p ≈ 1.4 for the Envision 4 MW turbine using LES and confirmed this value in a field experiment, although the number of data points beyond |γ| > 10 • were limited.…”

“…Kheirabadi & Nagamune (2019) 1 for a recent review). One wind farm control methodology which demonstrates potential in simulations 2,3 , lab experiments 4,5 , and field experiments [6][7][8][9] to increase collective turbine power production is wake steering, which entails the intentional yaw misalignment of turbines to deflect wake regions laterally away from downwind generators. The potential for wake steering to increase wind farm power production depends on the magnitude of wake interactions between the wind turbines, the magnitude of the wake deflection as a function of yaw misalignment, and the power production lost by the yaw misaligned turbines 10 .…”

“…Madsen et al (2020) 23 ), but these corrections are not necessarily known a priori or generally applicable. The challenge for BEM methods to predict P p , or more generally P r (γ) or C p (γ), necessitates its estimation through computationally expensive LES of wind turbine models (see discussion by Fleming et al (2017) 6 ).…”

Dynamic Strategies for Yaw and Induction Control of Wind Farms Based on Large-Eddy Simulation and Optimization

“…Static yaw control, in which upstream turbines intentionally misalign their rotors with incoming winds, has been proven as a promising approach to increasing power extraction, in numerical studies [25,26], but also in wind-tunnel tests [27,28] and full-scale field measurements [29,30]. Studies on dynamic yaw control however are much more scarce.…”

Enabling the SMART Wind Power Plant of the Future Through Science-Based Innovation

“…The study demonstrated the opportunity for an increase of a percent or more in annual energy production, which would result in revenue gains for wind plant owner/operators. The potential improvement has gained significant interest from industry and has led to multiple field campaigns involving industry-laboratory collaboration to prove the technology performance (for an example of field-test results in an offshore wind application, see Fleming et al 2017).…”