Energy Department Announces $2.5 Million to Improve Wind Forecasting

Due to the complexity of terrain in mountain-valley regions and varying degrees of soil moisture and surface temperatures, predicting specific wind conditions presents a major challenge to utility operators looking to optimize the performance of wind turbines in these areas. This funding will allow Vaisala and its partners to use advanced meteorological equipment to analyze specific environmental characteristics that affect wind flow patterns in the Columbia River Gorge region of Washington and Oregon.

Data collected during the project will be shared in near real-time with the National Oceanic and Atmospheric Administration (NOAA) and the Energy Department’s national laboratories, and will be used to develop improved atmospheric simulations for the Weather Research and Forecasting model, a widely used weather prediction system. These new wind measurements and simulations will also be incorporated into NOAA’s Numerical Weather Prediction models to improve short-term wind forecasts in complex terrain.

This important research builds on the Energy Department’s Wind Forecast Improvement Project, which previously explored wind energy resources in the northern Great Plains and western Texas. For the first time ever, NOAA, including cooperative institute colleagues, assimilated wind data from tall turbines and nacelle anemometers into meteorological models for use by the wind industry and other sectors. Integrating these new data into existing models produced forecasts that were up to 15 percent more accurate at predicting future wind conditions in nearly flat terrain.  

The Energy Department’s Office of Energy Efficiency and Renewable Energy accelerates development and deployment of energy efficiency and renewable energy technologies and market-based solutions that strengthen U.S. energy security, environmental quality, and economic vitality. Learn more about wind forecasting in the United States by visiting the Energy Department’s wind resource assessment and characterization webpage.