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CU-Boulder  >  College of Arts and Sciences  >  ATOC  >  Prof. Lundquist

Renewable Energy Projects

TWICS (Turbine Wake and Inflow Characterization Study): How do turbulent fluctuations in the atmosphere affect a wind turbine and its wake?

To promote the expansion of wind energy in the United States, advances in wind turbine technology are required to enhance reliability of existing turbines and ensure robust site-specific design of next-generation turbines. Improved understanding and characterization of inflow conditions on turbines in complex terrain would help engineers better understand, model, and design for turbine loading, turbine performance, and power plant performance. This improved understanding can develop from an integration of advanced observational capabilities with innovative approaches to atmospheric simulation. Our team, from CU-Boulder, NOAA ESRL's atmospheric remote sensing group, NREL NWTC, and LLNL, will deploy high-resolution atmospheric observations (from the High-Resolution Doppler lidar, or HRDL, as well as meteorological towers with sonic anemometers) in the vicinity of a modern 2.3 MW turbine. These unique observations will be coupled with advanced atmospheric modeling capabilities. High-resolution observations of modern turbine wakes will enable the development of large-scale wind farm forecasting models. This project is supported by the US Department of Energy Wind and Hydropower Technologies Program, "20% by 2030" and the Colorado Research and Education in Wind seed grant program.

Velocity Variance from HRDL
Figure showing streamwise velocity variance calculated from HRDL in staring mode at 10 degree elevation angle for approximately 8 minutes. Bottom strip: corresponding coherence turbulent kinetic energy measured by tower. Figure from Banta et al., 2008 and Kelley et al., 2006.

How does atmospheric stability impact wind turbine performance?

Using meteorological and power generation data from a West Coast North American wind farm over a one-year period, our study synthesizes standard wind park observations, such as wind speed from turbine nacelles and sparse meteorological tower observations, with high-resolution profiles of wind speed and turbulence from a remote sensing platform, to quantify the impact of atmospheric stability on wind turbine power output. Collaborators include Sonia Wharton and Iberdrola Renewables. Initial work presented at the International Energy Agency Topical Expert Meeting on "Remote Wind Speed Sensing Techniques Using SODAR and LIDAR and the AGU Fall Meeting. This project is supported by the US Department of Energy Wind and Hydropower Technologies Program, Renewable Systems Interconnect Support.

GE 1.5 MW turbines at Desert Sky, image from http://www.gepower.com/businesses/ge_wind_energy/en/image_gallery/clearsky.htm
GE wind turbines at a Texas wind farm, not related to the present studies

How can atmospheric models predict wind farm performance?

With data from an operating wind farm, we and colleagues at LLNL, UC-Berkeley, and Colorado School of Mines, are testing the ability of numerical weather prediction models and large eddy simulations to capture the wind fluctuations that challenge power grid operators. Our teams have modified standard models to improve representations of atmospheric turbulence and surface-atmosphere interaction, and are challenging the models by attempting to simulate ramping events in which wind speed changes so dramatically that the power at the wind farm fluctuates by over 50% in an hour. This project is supported by the US Department of Energy Wind and Hydropower Technologies Program, Renewable Systems Interconnect Support.