skip to main content
OSTI.GOV title logo U.S. Department of Energy
Office of Scientific and Technical Information

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

Journal Article · · Wind Energy Science (Online)
 [1];  [2]; ORCiD logo [3];  [4];  [3]
  1. Univ. of Colorado, Boulder, CO (United States). Dept. of Atmospheric and Oceanic Sciences (ATOC)
  2. Univ. of Colorado, Boulder, CO (United States). Dept. of Atmospheric and Oceanic Sciences (ATOC); National Renewable Energy Lab. (NREL), Golden, CO (United States)
  3. National Renewable Energy Lab. (NREL), Golden, CO (United States)
  4. V-Bar, LLC, Golden, CO (United States)

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.

Research Organization:
National Renewable Energy Laboratory (NREL), Golden, CO (United States)
Sponsoring Organization:
USDOE Office of Energy Efficiency and Renewable Energy (EERE), Wind and Water Technologies Office (EE-4W)
Grant/Contract Number:
AC36-08GO28308
OSTI ID:
1324230
Report Number(s):
NREL/JA-5D00-66360
Journal Information:
Wind Energy Science (Online), Vol. 1, Issue 2; ISSN 2366-7451
Publisher:
European Wind Energy Association - CopernicusCopyright Statement
Country of Publication:
United States
Language:
English

References (30)

Performance of a Wind-Profiling Lidar in the Region of Wind Turbine Rotor Disks journal March 2012
Quantifying Wind Turbine Wake Characteristics from Scanning Remote Sensor Data journal April 2014
Wind Shear and Uncertainties in Power Curve Measurement and Wind Resources journal October 2009
Implications of Small-Scale Flow Features to Modeling Dispersion over Complex Terrain journal March 1996
Conically scanning lidar error in complex terrain [Conically scanning lidar error in complex terrain] journal May 2009
A new formulation for rotor equivalent wind speed for wind resource assessment and wind power forecasting: New formulation for equivalent wind speed journal September 2015
Data Clustering Reveals Climate Impacts on Local Wind Phenomena journal August 2012
Using machine learning to predict wind turbine power output journal April 2013
Turbine Inflow Characterization at the National Wind Technology Center journal May 2013
Testing and comparison of lidars for profile and turbulence measurements in wind energy journal May 2008
Atmospheric Impacts on Power Curves of Multi-Megawatt Offshore Wind Turbines journal December 2014
How to improve the estimation of power curves for wind turbines journal January 2008
Turbulence Correction for Power Curves book January 2007
Quantifying error of lidar and sodar Doppler beam swinging measurements of wind turbine wakes using computational fluid dynamics journal January 2015
The influence of non-logarithmic wind speed profiles on potential power output at Danish offshore sites journal January 2005
Turbulent fluxes, stability and shear in the offshore environment: Mesoscale modelling and field observations at FINO1 journal November 2012
The Interaction of Katabatic Flow and Mountain Waves. Part I: Observations and Idealized Simulations journal June 2000
The Interaction of Katabatic Flow and Mountain Waves. Part II: Case Study Analysis and Conceptual Model journal June 2007
The Effect of Wind-Turbine Wakes on Summertime US Midwest Atmospheric Wind Profiles as Observed with Ground-Based Doppler Lidar journal July 2013
Temporal Coherence: A Model for Non-stationarity in Natural and Simulated Wind Records journal February 2016
An Introduction to Boundary Layer Meteorology book January 1988
Influence of Atmospheric Stability on Wind Turbine Power Performance Curves journal February 2006
Wind turbine power and sound in relation to atmospheric stability journal January 2008
The modification of wind turbine performance by statistically distinct atmospheric regimes journal September 2012
The influence of the wind speed profile on wind turbine performance measurements journal May 2009
Atmospheric stability affects wind turbine power collection journal January 2012
Assessing atmospheric stability and its impacts on rotor-disk wind characteristics at an onshore wind farm journal July 2011
Characterization of the unsteady flow in the nacelle region of a modern wind turbine journal March 2011
Turbine Inflow Characterization at the National Wind Technology Center
  • Clifton, Andrew; Schreck, Scott; Scott, George
  • 50th AIAA Aerospace Sciences Meeting including the New Horizons Forum and Aerospace Exposition https://doi.org/10.2514/6.2012-658
conference November 2012
Testing and comparison of lidars for profile and turbulence measurements in wind energy journal May 2008

Cited By (12)

Quantification of power losses due to wind turbine wake interactions through SCADA, meteorological and wind LiDAR data: Power losses due to wake interactions through SCADA, met and LiDAR data journal June 2017
Benchmarks for Model Validation based on LiDAR Wake Measurements journal July 2019
Using field data–based large eddy simulation to understand role of atmospheric stability on energy production of wind turbines journal January 2019
Modeling of the atmospheric boundary layer under stability stratification for wind turbine wake production journal October 2019
Modified Power Curves for Prediction of Power Output of Wind Farms journal May 2019
An Induction Curve Model for Prediction of Power Output of Wind Turbines in Complex Conditions journal February 2020
Characterization of Turbulence in Wind Turbine Wakes under Different Stability Conditions from Static Doppler LiDAR Measurements journal March 2017
Atmospheric turbulence affects wind turbine nacelle transfer functions posted_content December 2016
Free-flow wind speed from a blade-mounted flow sensor journal January 2018
More accurate aeroelastic wind-turbine load simulations using detailed inflow information journal January 2019
The effect of wind direction shear on turbine performance in a wind farm in central Iowa journal January 2020
Atmospheric turbulence affects wind turbine nacelle transfer functions journal January 2017