Atmospheric turbulence affects wind turbine nacelle transfer functions

Abstract

Abstract. Despite their potential as a valuable source of individual turbine power performance and turbine array energy production optimization information, nacelle-mounted anemometers have often been neglected because complex flows around the blades and nacelle interfere with their measurements. This work quantitatively explores the accuracy of and potential corrections to nacelle anemometer measurements to determine the degree to which they may be useful when corrected for these complex flows, particularly for calculating annual energy production (AEP) in the absence of other meteorological data. Using upwind meteorological tower measurements along with nacelle-based measurements from a General Electric (GE) 1.5sle model, we calculate empirical nacelle transfer functions (NTFs) and explore how they are impacted by different atmospheric and turbulence parameters. This work provides guidelines for the use of NTFs for deriving useful wind measurements from nacelle-mounted anemometers. Corrections to the nacelle anemometer wind speed measurements can be made with NTFs and used to calculate an AEP that comes within 1 % of an AEP calculated with upwind measurements. We also calculate unique NTFs for different atmospheric conditions defined by temperature stratification as well as turbulence intensity, turbulence kinetic energy, and wind shear. During periods of low stability as defined by the Bulk Richardson number (RB), the nacelle-mounted anemometer underestimates the upwind wind speed more than during periods of high stability at some wind speed bins below rated speed, leading to a more steep NTF during periods of low stability. Similarly, during periods of high turbulence, the nacelle-mounted anemometer underestimates the upwind wind speed more than during periods of low turbulence at most wind bins between cut-in and rated wind speed. Based on these results, we suggest different NTFs be calculated for different regimes of atmospheric stability and turbulence for power performance validation purposes.

Observing and Simulating Wind-Turbine Wakes During the Evening Transition

“…Thus, this study lays the groundwork for future investigations to compare the power output of the WFP scheme to the observed power production, which can be conducted with nacelle anemometer measurements (St. Martin et al 2017). Since mesoscale modelling is crucial in predicting power production in wind farms (Marquis et al 2011;Jiménez et al 2015;Wilczak et al 2015), comparisons of predicted and observed power output can help to identify areas for improvement in the WFP scheme in the WRF model.…”

Incoming flow measurements of a utility-scale wind turbine using super-large-scale particle image velocimetry

“…After phase averaging, all the velocity components exhibit signatures of blades passing with its intensity decreasing away from the rotor plane. Martin et al [39] reported different atmospheric conditions (e.g. stratification and turbulence intensity, etc.)…”

Nacelle anemometer measurement‐based extremum‐seeking wind turbine region‐2 control for improved convergence in fluctuating wind

“…The NTF is essentially a mapping from the wind speed measurement of nacelle‐top anemometer to the FSWS measured with met‐tower anemometry. Earlier work shows that the NTF‐based FSWS estimation achieves an R 2 (coefficient of determination) of 0.98 for a linear regression and 0.99 for a fifth‐order polynomial fitting . The annual energy production (AEP) calculated by the NTF‐based FSWS estimation yields an error less than 1% than that based on met‐tower measurement .…”

“…Earlier work shows that the NTF‐based FSWS estimation achieves an R 2 (coefficient of determination) of 0.98 for a linear regression and 0.99 for a fifth‐order polynomial fitting . The annual energy production (AEP) calculated by the NTF‐based FSWS estimation yields an error less than 1% than that based on met‐tower measurement . In particular, the use of spinner anemometer installed at the hub cover has shown more accurate and reliable FSWS estimation for upwind turbines …”

“…This proof‐of‐concept study is performed with control simulation using FAST, the wind turbine aeroelastic simulation software by NREL. In this study, on the basis of the acceptance of the validity of the NTF method in the existing literatures, we assume that the FSWS can be obtained with a no‐bias estimation but contaminated with some white noise whose variance is similar to that of the regression errors in the aforementioned literatures. A comparative study later reveals that the improvement in ESC performance will not be compromised by a moderate level error in the FSWS estimation.…”