Wind’s contribution to energy production in the United States continues to grow. In 2011, it represented a third of all new electric generating capacity. Individual wind turbines are getting larger in power-generating capacity, hub height, and rotor diameter—largely in order to make wind turbines viable in areas with lower wind speeds. This growth is expected to continue.
Decisions about where to site commercial-scale wind turbines—typically costing $3-4 million each installed (though their cost drops significantly with economies of scale for large wind farms)—require detailed, reliable, and long-term data about wind speed and direction. Wind speed maps and tables published by the National Renewable Energy Laboratory (NREL), the U.S. Department of Energy’s primary laboratory for renewable energy and energy efficiency research and development, are a good starting point.
However, resource assessment (to identify locations with sufficient wind speeds for turbines to work efficiently) and forecasting (to know whether the longterm average wind speeds make investments in wind energy cost-effective) require much more detailed knowledge of local wind conditions. Additionally, realtime measurements of the speed of approaching wind gusts, fed into the turbines’ control systems, can enable them to instantly adjust the gears so as to maximize energy production while minimizing the chance of mechanical failure.
Currently, the two preferred technologies for collecting wind data are ground-based SoDAR and LiDAR.