Ultra-Accurate Forecasts Help Utilities Harness the Wild Wind

The forecasts will help operators make critical decisions about powering down coal-fired and natural gas-fired plants when sufficient winds are predicted to generate the required amount of electricity to serve Xcel customers.

"One of the major obstacles that has prevented more widespread use of wind energy is the difficulty in predicting when and how strongly the wind will blow at the wind farms," says William Mahoney, the NCAR program director overseeing the project. "These forecasts are a critical step in getting more energy from wind."

The National Renewable Energy Laboratory based in Golden, Colorado will support the project by developing mathematical formulas to calculate the amount of energy that turbines generate when winds blow at various speeds.

"The utility is interested in the potential power coming from these large wind sites, but every wind turbine on the site will not have the same wind speed," says NREL engineer Erik Ela. "NREL's models will convert the wind speed into power and give the utility better information on how much electricity the entire wind site will generate."

Rows of turbines at sunset at Ponnequin Wind Facility in Weld County, Colorado (Photo by Jenny Hager Photography courtesy NREL)

Wind is difficult to forecast as it is affected by topography, ground cover, temperature inversions, even the number of leaves on nearby trees. To make the task more challenging, wind turbines are between 200 to 400 feet above the ground and arrayed in tightly clustered wind farms. Winds at these heights are usually far stronger than at 33 feet, the height used by ground-level weather stations.

Yet many states are requiring utilities to use renewable energy to reduce dependence on coal, oil, and natural gas, which affect air quality and release greenhouse gases associated with climate change.

Because large amounts of electricity cannot be stored cost-effectively, power generated by a wind turbine or any other source must be promptly used.

If a utility powers down a coal-fired or natural gas-fired facility in anticipation of wind-driven energy, those plants may not be able to power up fast enough when winds fail to blow. Then the utility must buy energy on the spot market, which can be expensive. Yet, if the winds blow more strongly or erratically than anticipated, the surge of energy can overload the system.

"Wind energy remains difficult to manage due to its variability - you can't always count on it," says Eric Pierce, Xcel Energy's managing director of energy trading. "Accurately forecasting our wind power generation will allow Xcel Energy to reliably bring on more wind energy and reduce costs at the same time. This is an important part of building a 21st century energy system."

Under the agreement, NCAR will develop a prototype advanced wind prediction system during the next 18 months and will begin to generate test forecasts for Xcel Energy wind farms in Colorado, Minnesota, New Mexico, Texas, and Wyoming after six months.

NCAR will continue to improve the system over the following 12 months. Then the prototpe forecasting system will be transferred to Xcel Energy for operational use, while NCAR continues to work toward making the forecasts still more accurate.

To generate the forecasts, NCAR will incorporate observations of current atmospheric conditions from satellites, aircraft, weather radars, ground-based weather stations, and sensors on the wind turbines.

The project builds on forecast technologies that NCAR has successfully developed for the U.S. military, National Weather Service, aviation industry, overseas governments, and other organizations in the public and private sectors.

NCAR scientists will first feed the information into the Weather Research and Forecasting computer model, which generates finely detailed simulations of future atmospheric conditions.

Then the simulations will go to the Real-Time Four-Dimensional Data Assimilation System, which continuously updates the simulations with the most recent observations.

Finally, the updated simulations will be fed into the Dynamic Integrated foreCast System, which statistically optimizes the output based on recent performance.

"Wind can be elusive, and even very small changes in the atmosphere can make a difference in wind speed and direction," Mahoney says. "But we believe our experience in developing increasingly sophisticated forecasting systems will enable us to produce the accurate forecasts that Xcel Energy needs to provide reliable wind energy to its customers."

If the prediction system is successful, wind forecasting companies may adopt the technology to help utilities in the United States and overseas transition away from fossil fuels.

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