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Spiral 2: 3/28/2011Department of Defense Energy HandbookAlternative and Renewable Energy Options for DoD Facilities and BasesTable 46. Wind speed classifications by vertical extrapolation. 194Wind PowerClassWind PowerDensity (W/m 2 )10 m (33 ft) 50 m (164 ft)Speed m/s(mph)Wind PowerDensity (W/m 2 )Speed m/s (mph)0 0 0 0 01 100 4.4 (9.8) 200 5.6 (12.5)2 150 5.1 (11.5) 300 6.4 (14.3)3 200 5.6 (12.5) 400 7.0 (15.7)4 250 6.0 (13.4) 500 7.5 (16.8)5 300 6.4 (14.3) 600 8.0 (17.9)6 400 7.0 (15.7) 800 8.8 (19.7)7 1000 9.4 (21.1) 2000 11.9 (26.6)A minimum of two years of data are needed to obtain an estimate for the annual wind power potential,and five years of data are needed to obtain a mean value within six percent of the long-term mean.However, it is generally accepted that two to three years of data combined with regional data is enoughto generate an accurate estimate of wind power potential. Where long-term regional data is available,accurate assumptions can be made using only one to two years of data for a specific location.Wind power potential is generated using wind speed data. There have been many past efforts to createwind maps for aiding in early development efforts. Some of the first maps were generated in the 1990’s.This data varied greatly in accuracy from location to location due to inconsistencies in data. Windspeeds were taken at various ground heights, which depended on height of the building or availablestructures to place metering devices. One of the greatest shortfalls is that much of the wind data usedto produce maps in the past was taken at heights lower than modern turbines being designed today (i.e.,30 meters or less), which have been evolving to much greater heights. Also, wind data used in earlymaps was collected at different intervals and could have been recorded hourly, daily, or even monthly.These variables greatly affect average wind speed calculation and power potential. However, they stillprovided some insight for researchers and developers in determining beneficial locations. Generally,smaller state and local maps yielded more accurate data since data collection was more consistent.There have been efforts to modernize wind maps and improve the accuracy of data being used to meetthe requirements of current technology. A project by NREL and AWS Truewind called windNavigatorhas improved wind map accuracies. lvii The wind data was collected at a consistent 80 m ground height,(previous maps had a maximum 50 m tower height), and wind speeds were collected at geographicpoints 200 m apart. Graphical data as presented on a map is shown in Figure 102. Advanced meteringcombined with modeling and simulation is improving the development timeframe by providing moreaccurate assessments in less time.lviiAWS Truewind windNavigator. https://www.windnavigator.com171
Spiral 2: 3/28/2011Figure 102.Graphical representation for the transition toward larger and taller wind turbinesfor propeller style HAWT designs. 195For utility power production, wind power depends very heavily on proximity to a power grid and thestate of existing power resources. Most wind farms work in cooperation with a power utility tosupplement existing energy supply. Access roads and transmission lines are a major cost to consider fornew site development. Many commercial development sites to date have been located near availabletransmission. Developers are currently trying to work with government agencies to find affordable waysto create new transmission lines that will make future wind projects possible.9.8.1 Radar Interference and Air Traffic Control IssuesInterference with military and weather radar is also an important concern for siting wind projects. Thisinterference has led the Federal Aviation Administration (FAA), the Department of Homeland Security(DHS), and the DoD to contest many proposed wind turbines in the line-of-sight of radar, stalling thedevelopment of several thousands of MW capacity of wind energy. A large number of such denials is aserious impediment to the nation’s mandated growth of sustainable energy. There is no fundamentalphysical constraint that prohibits the accurate detection of aircraft and weather patterns around windfarms. However, the nation’s aging long range radar infrastructure significantly increases the challenge ofdistinguishing wind farm signatures from airplanes or weather.Progress forward requires the development of mitigation measures, and quantitative evaluation toolsand metrics to determine when a wind farm poses a sufficient threat to a radar installation forcorrective action to be taken. Mitigation measures may include modifications to wind farms, such asmethods to reduce radar cross section and telemetry from wind farms to radar, as well as modificationsto radar, such as improvements in processing, radar design modifications, radar replacement, and theuse of gap fillers in radar coverage.172
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