Accurate wind power forecasts are crucial in order for wind farm operators to manage operations, meet regulatory requirements, reduce penalties and losses, and maximize revenue. Yet wind power production is difficult to forecast accurately. Wind power itself scales with the cube of the wind speed, and the response of a wind turbine is a complex power output curve. Depending on wind speed and the characteristics of the wind turbine, abrupt changes in wind speed (“ramps”) can cause large changes in power output. Complex terrain and meteorological phenomena such as low-level jets, land-sea breezes, and thunderstorm winds increase the forecasting challenge.

In 2008, Weather Decision Technologies, Inc. (WDT), and NanoWeather, Inc., became part of a consortium of academic, public, and private enterprises that was awarded a significant two-year grant from the State of Oklahoma’s Economic Development Generating Excellence (EDGE) program. The consortium is led by the University of Oklahoma’s Oklahoma Wind Power Initiative (OWPI). The grant was made to WDT and NanoWeather to conduct research into and to develop a wind energy forecast and assessment system in support of the state’s rapidly growing wind energy industry.

Specifically, WDT and NanoWeather are combining their areas of core expertise to produce WindPredictor™, a unified forecasting system ideally suited for wind power forecasting. WDT brings its knowledge and expertise in years of operational mesoscale forecasting, notably the Weather Research and Forecasting (WRF) Model. WDT was an early adopter of WRF and was the first company to deploy WRF internationally.

NanoWeather brings the Uncoupled Surface Layer (USL) Model, a microscale numerical weather prediction (NWP) model that focuses entirely on conditions in the lowest levels of the atmosphere. This forecast model regularly beats all other models, and the vast majority of human forecasters, at WxChallenge, the North American collegiate weather forecasting contest. It was awarded the Grand Prize at the 2006 Collegiate Inventors Competition.

The combination of mesoscale (WRF) and microscale (USL) models forms the core of WindPredictor™. Other components include: a forecast ensemble system; a web-based user interface; skill scores for recent forecasts; and a method for detecting and predicting wind ramps. WindPredictor™ can utilize observational data from many sources, including instrumented meteorological towers, sodars, lidars, thermodynamic profiling radars, and wind power measurements.

LDSS

To enhance protection of renewable energy assets, our Lightning Decision Support (LDSS) solution is a complete weather package, utilizing a wide array of WDT's proprietary weather and lightning technologies. Now you can have advanced severe weather tracking, real-time lightning, lightning prediction, site-specific alerting, ice and snow monitoring technologies, and tropical storm tracking all in one concise service.

For more information, contact

Dax Cochran (405) 801.3910 or
Dr. Richard Carpenter (405) 579. 7675 x229

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