Wind turbine power production and annual energy production depend on atmospheric stability and turbulence

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.

[1]  George Scott,et al.  Turbine Inflow Characterization at the National Wind Technology Center , 2013 .

[2]  J. Lundquist,et al.  The modification of wind turbine performance by statistically distinct atmospheric regimes , 2012 .

[3]  T. McCoy,et al.  Applicability of Nacelle Anemometer Measurements for Use in Turbine Power Performance Tests: Preprint , 2002 .

[4]  Ronald Calhoun,et al.  A new formulation for rotor equivalent wind speed for wind resource assessment and wind power forecasting , 2016 .

[5]  Julie K. Lundquist,et al.  Data Clustering Reveals Climate Impacts on Local Wind Phenomena , 2012 .

[6]  J. Lundquist,et al.  Assessing atmospheric stability and its impacts on rotor‐disk wind characteristics at an onshore wind farm , 2010 .

[7]  Frank Scheurich,et al.  Improving the Accuracy of Wind Turbine Power Curve Validation by the Rotor Equivalent Wind Speed Concept , 2016 .

[8]  J. van Beeck,et al.  Turbulent fluxes, stability and shear in the offshore environment: Mesoscale modelling and field observations at FINO1 , 2012 .

[9]  Neil Kelley,et al.  Lidar Investigation of Atmosphere Effect on a Wind Turbine Wake , 2013 .

[10]  G. P. van den Berg,et al.  Wind turbine power and sound in relation to atmospheric stability , 2008 .

[11]  R. Stull.  An Introduction to Boundary Layer Meteorology , 1988 .

[12]  R. Pielke,et al.  The Interaction of Katabatic Flow and Mountain Waves. Part II: Case Study Analysis and Conceptual Model , 2007 .

[13]  Julie K. Lundquist,et al.  The Effect of Wind-Turbine Wakes on Summertime US Midwest Atmospheric Wind Profiles as Observed with Ground-Based Doppler Lidar , 2013, Boundary-Layer Meteorology.

[14]  Julie K. Lundquist,et al.  Performance of a Wind-Profiling Lidar in the Region of Wind Turbine Rotor Disks , 2010 .

[15]  Ioannis Antoniou,et al.  The influence of the wind speed profile on wind turbine performance measurements , 2009 .

[16]  Julie K. Lundquist,et al.  Quantifying error of lidar and sodar Doppler beam swinging measurements of wind turbine wakes using computational fluid dynamics , 2015 .

[17]  P. H. Gudiksen,et al.  Implications of Small-Scale Flow Features to Modeling Dispersion over Complex Terrain. , 1996 .

[18]  Julie K. Lundquist,et al.  Quantifying Wind Turbine Wake Characteristics from Scanning Remote Sensor Data , 2014 .

[19]  Julia Gottschall,et al.  Can wind lidars measure turbulence , 2011 .

[20]  Martin Kühn,et al.  Atmospheric Impacts on Power Curves of Multi-Megawatt Offshore Wind Turbines , 2014 .

[21]  James M. Bleeg,et al.  EFFECTS OF COMPLEX WIND REGIMES ON TURBINE PERFORMANCE , 2009 .

[22]  J. Mann,et al.  Conically scanning lidar error in complex terrain , 2009 .

[23]  Ioannis Antoniou,et al.  Wind Shear and Uncertainties in Power Curve Measurement and Wind Resources , 2009 .

[24]  Rebecca J. Barthelmie,et al.  The influence of non‐logarithmic wind speed profiles on potential power output at Danish offshore sites , 2005 .

[25]  K. Kaiser,et al.  Turbulence Correction for Power Curves , 2007 .

[26]  Jennifer M. Rinker,et al.  Temporal Coherence: A Model for Non-stationarity in Natural and Simulated Wind Records , 2016, Boundary-Layer Meteorology.

[27]  Paul Fleming,et al.  Using machine learning to predict wind turbine power output , 2013 .

[28]  R. Pielke,et al.  The Interaction of Katabatic Flow and Mountain Waves. Part I: Observations and Idealized Simulations , 2000 .

[29]  J. W. Wagenaar,et al.  Dependence of Power Performance on Atmospheric Conditions and Possible Corrections , 2011 .

[30]  William A. Gallus,et al.  Characteristics of 50–200-m Winds and Temperatures Derived from an Iowa Tall-Tower Network , 2014 .

[31]  Niels N. Sørensen,et al.  Characterization of the unsteady flow in the nacelle region of a modern wind turbine , 2011 .

[32]  F. Guillén,et al.  Multi-site testing and evaluation of remote sensing instruments for wind energy applications , 2013 .

[33]  H. Jørgensen,et al.  Wind lidar evaluation at the Danish wind test site in Høvsøre , 2006 .

[34]  Neil D. Kelley,et al.  Turbulence-Turbine Interaction: The Basis for the Development of the TurbSim Stochastic Simulator , 2011 .

[35]  Troels Friis Pedersen,et al.  European wind turbine testing procedure developments. Task 1: Measurement method to verify wind turbine performance characteristics , 2001 .

[36]  Ismael Mendoza,et al.  Power Performance Test Report for the U.S. Department of Energy 1.5-Megawatt Wind Turbine , 2015 .

[37]  Per Jonas Petter Lindelöw,et al.  Testing and comparison of lidars for profile and turbulence measurements in wind energy , 2008 .

[38]  Joachim Peinke,et al.  How to improve the estimation of power curves for wind turbines , 2008 .

[39]  Christian Masson,et al.  Influence of atmospheric stability on wind turbine power performance curves , 2006 .

[40]  J. Lundquist,et al.  Atmospheric stability affects wind turbine power collection , 2011 .

[41]  Jens Nørkær Sørensen,et al.  The generics of wind turbine nacelle anemometry , 2009 .

[42]  D. L. Elliott,et al.  Effects of wind shear and turbulence on wind turbine power curves , 1990 .