Abstract
Abstract. Using detailed upwind and nacelle-based measurements from a General Electric (GE) 1.5sle model with a 77 m rotor diameter, we calculate power curves and annual energy production (AEP) and explore their sensitivity to different atmospheric parameters to provide guidelines for the use of stability and turbulence filters in segregating power curves. The wind measurements upwind of the turbine include anemometers mounted on a 135 m meteorological tower as well as profiles from a lidar. We calculate power curves for different regimes based on turbulence parameters such as turbulence intensity (TI) as well as atmospheric stability parameters such as the bulk Richardson number (RB). We also calculate AEP with and without these atmospheric filters and highlight differences between the results of these calculations. The power curves for different TI regimes reveal that increased TI undermines power production at wind speeds near rated, but TI increases power production at lower wind speeds at this site, the US Department of Energy (DOE) National Wind Technology Center (NWTC). Similarly, power curves for different RB regimes reveal that periods of stable conditions produce more power at wind speeds near rated and periods of unstable conditions produce more power at lower wind speeds. AEP results suggest that calculations without filtering for these atmospheric regimes may overestimate the AEP. Because of statistically significant differences between power curves and AEP calculated with these turbulence and stability filters for this turbine at this site, we suggest implementing an additional step in analyzing power performance data to incorporate effects of atmospheric stability and turbulence across the rotor disk.
Highlights
Power performance testing and annual energy production (AEP) assessments rely on accurate calculations of wind turbine power curves
We investigate the influence of different atmospheric stability and turbulence regimes on wind turbine power curves and AEP calculations, incorporating a broad set of atmospheric parameters as well as different approaches to measuring these parameters
The lower AEP calculated when separating by stability and turbulence regimes suggests that the AEP calculated using no filters may be overestimating the production, perhaps because the higher and lower extremes of the parameter ranges bias the averages in each bin
Summary
Power performance testing and annual energy production (AEP) assessments rely on accurate calculations of wind turbine power curves. Previous work on power performance highlights the role of turbulence intensity (TI) and wind shear in influencing power production (Elliot and Cadogan, 1990; Hunter et al, 2001; Kaiser et al, 2003; Sumner and Masson, 2006; Gottschall and Peinke, 2008; Antoniou et al, 2009; Rareshide et al, 2009; Wharton and Lundquist, 2012a, b; Clifton et al, 2013a; Dörenkämper et al, 2014). Wharton and Lundquist (2012b) found that vertical TI and turbulence kinetic energy (TKE) affect power performance and Rareshide et al (2009) found that veer affects power performance.
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