2024-10-16
http://w3.windfair.net/wind-energy/pr/9218-usa-wind-turbine-operators-increase-efficiency-of-systems-by-using-accurate-information-and-models-on-wind-direction-changes

USA - Wind turbine operators increase efficiency of systems by using accurate information and models on wind direction changes

“Weather information must provide power purchasers with a forecast for tomorrow’s electrical production at hourly intervals”

Wind farm operators need a bit more detail in their weather forecasts than the evening news offers. “Weather information must provide power purchasers with a forecast for tomorrow’s electrical production at hourly intervals,” says Dr. Dan Kirk-Davidoff, chief scientist, climate and weather services for MDA Information Systems Inc, in Washington, DC. “That requires a wind forecast at the height and location of each turbine hub, about 80 m above ground.”

Ideally, forecasts would be more finely spaced in time, so that they could predict ramp events, sudden increases or decreases in wind speed. This may never be possible for the day-ahead forecast. However, Kirk-Davidoff says there is strong emphasis on increasing time resolution in the three-hour forecast so operators have some warning of these ramps. Operators are also interested in events that would impact their ability to run the turbines. “For example, turbines must shut down when wind speeds exceed a ‘cut-out’ threshold, typically 25 meters per second,” he says. “Icing from freezing rain can also lower turbine efficiency.”

Finally, turbine operators can squeeze a little extra efficiency out of their systems with a few minutes warning of a change in wind direction. Kirk-Davidoff says this is possible using on-site remote-sensing equipment to measure Doppler shifts of sound (SODAR). or laser light (LIDAR) bounced off of temperature variations or dust motes in the atmosphere.

MDA Information Systems provides wind speed and turbine power predictions from the present through the following five days. “We provide a live web display, text-file data feeds, and .pdf documents that include maps and a discussion of the forecast,” he says. This goes to wind farm site managers, utility power purchasers, and for our aggregate wind power forecasts, the ERCOT and Midwest ISO electrical markets, and energy traders.

Windfarm operators use the forecast to provide power purchasers with a day-ahead predictions of their expected contribution to the electrical grid. “Power purchasers and energy traders use the forecast information to plan their needs for power generation other than wind. For example, they might plan purchases of natural gas to generate electric power or predict the price of electricity in the day-ahead market,” adds Kirk-Davidoff.

Demand for accurate weather data has grown tremendously in the last 5 to 10 years with wind-power generation growing fastest. The installed wind-power capacity has increased from 2.5 GW in 2000 to 40 GW in 2010. “Forecasting has become more sophisticated because weather models have increased in spatial resolution and skill,” he says. “Also, meteorologists have built up statistics that relate computer forecasts at grid points to observed winds at individual turbines. What’s more, turbine operators have higher expectations about wind-power-forecast accuracy,” he says.

“The cutting edge of wind power forecasting, as for all weather modeling, is the data assimilation process,” says Kirk-Davidoff. “We need to increase the volume of surface and upper air wind data we incorporate into weather forecast models, and improve the accuracy with which we do this, to continue to improve our forecast skill.”

For more information on this article or if you would like to know more about what www.windfair.net can offer, please do not hesitate to contact Trevor Sievert at ts@windfair.net

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Source:
MDA Information Federal
Author:
Posted by Trevor Sievert, Online Editorial Journalist
Email:
ts@windfair.net
Link:
www.windfair.net/...
Keywords:
wind, wind energy, wind turbine, rotorblade, awea, ewea, wind power, suppliers, manufacturerstrevor sievert




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