1. 12.0 Wind Energy, Part 1 Frank R. Leslie, B. S. E. E., M. S. Space Technology, LS IEEE 2/23/2010, Rev. 2.0.3 fleslie @fit.edu; (321) 674-7377 www.fit.edu/~fleslie Wind Resources

2. In Other News... Pres. Obama gives $8 billion in loan guarantees to Burke County GA nuclear plant to start Norway experimenting with Statkraft osmotic pressure hydro plant at Tofte producing 4 kW  http://www.newscientist.com/article/dn18204-first-osmosis-power-plant-goes-on-stream-in- norway.html http://www.newscientist.com/article/dn18204-first-osmosis-power-plant-goes-on-stream-in- norway.html Florida Flywheelers show on Saturday, 2/25/10  http://www.youtube.com/watch?v=myu2Dmv1mOQ http://www.youtube.com/watch?v=myu2Dmv1mOQ  Between Ft. Meade and Frostproof, FL 100223

3. 12 Overview: Wind Resources Class Wind Sessions:  Wind Resources, Part 1  Wind Energy Theory, Part 2  Wind Turbine Theory, Part 1  Wind Turbine Practice, Part 2  Hybrid Wind Systems Wind resources are distributed unevenly around the World Wind “Prospecting” shows where higher (economically useful) winds are located Wind passage is measured in miles (or km) of wind per hour or per day; divide to get miles per hour average 060212

4. 12.0 About This Presentation 12.0.1 Wind Resources 12.0.2 US State Wind Maps 12.0.3 European Wind Maps 12.0.4.1 Other Areas: India 12.0.5.1 Wind Statistics 12.0.6.1 Wind Analysis 12.0 Conclusion 060212

5. 12.0.1 Wind Energy as Detected by Turbine Presence Favorable California tax incentives resulted in major U.S. wind farms  Altamonte Pass  Tehachapi  San Gorgonio Pass Other turbines are located in Dakotas, Iowa, OR, Texas, Minnesota, NY, WA, Wyoming, Iowa, PA, VA, Vermont, etc. www.nrel.gov/wind/usmaps.html 100212 Larger view on following slide

6. 12.0.2 Wind Resources (a larger view) 030220

7. 12.0.2.1 Idaho Commercial wind mappers have extended the definition of windmaps using topographic information

8. 12.0.2.1 Idaho Wind Power by Top Counties

9. 12.0.2.1 Idaho Wind Speed and Power Maps http://www.windpowermaps.org/windmaps/IDwindpower50_big.htm

10. 12.0.2.2 Washington 030220 http://www.windpowermaps.org/windmaps/states.asp

11. 12.0.2.3 Oregon http://www.windpowermaps.org/windmaps/states.asp 060212

12. 12.0.2.5 Montana http://www.windpowermaps.org/windmaps/states.asp 060212

13. 12.0.2.6 Northeast United States The Cape Wind Project is planned for the red area near Nantucket MA Wind power density is shown rather than wind speed The strong red density shows high power that is economical

14. 12.0.2.7 New York (Lake Effect Example) http://www.awstruewind.com/inner/windmaps/maps/NorthAmerica/UnitedStates 100218

15. 12.0.2.8 South Carolina (Ocean Example) http://www.awstruewind.com/inner/windmaps/maps/NorthAmerica/UnitedStates 100218

16. 12.0.2.9 Wyoming 030220 http://www.windpowermaps.org/windmaps/states.asp

17. 12.0.2.10 Wind Energy in Texas AEI 030220

18. 12.0.2.11 Wind Energy Is Best Suited to the Great Plains States Coastal Florida has Class 2 wind energy (160 to 240 W/m^2) per the PNNL Wind Energy Atlas ― sufficient to investigate but marginal for major wind energy systems High average wind speeds in the Rocky Mountain Region (300 to 1000 W/m^2) and the Great Plains States (200 to 250 W/m^2) improve economics 050215

19. 12.0.2.11.1 Florida Has Marginal Wind Energy These wind energy maps are available for each state and for the World Coastal Florida is Class 2 with seabreeze and storm front passages Summer ground heating results in ~10 mph seabreezes and storms Winter is calmer, with frontal storm passages averaging every four days From the PNNL Wind Energy Atlas 060212

20. 12.0.3.1 Europe Wind Resource http://www.windpower.dk/tour/wres/euromap.htm030220

21. 12.0.3.2 France http://home.planet.nl/~windsh/windmapofFrance.jpg030220

22. 12.0.4.1 India 060212http://www.windpowerindia.com/statwind.asp

23. 12.0.5.1 Wind Statistics and Assessment Wind speed and direction are measured by an anemometer  Speed is derived from rotating cups or a spinning propeller driving an interrupter device or a small electric generator  Data are logged electronically for later processing The mean (average) and peak (gust) speeds are of the greatest importance Turbulence may affect turbine efficiency, but yawing points the turbine into the average wind  Ten-minute averages are used for power assessment, while gust studies may require two to ten points per second 060212

24. 12.0.6.1 A Sample Day’s Sea Breeze Wind Profile From the FSEC MET System in Cocoa, FL Ref.: FSEC Effective wind is from 9 a.m. to ~5 p.m. 030219

25. 12.0.6.1 Roberts Hall 103 ft Wind Gusts 2/13/08 Wind gusts reached 32 mph at 103 ft during a storm passage Gust measured as highest one- second value in a minute Data logged each second and averages created for each minute 100222

26. 12.0.5.2 Wind Statistics and Assessment Dataloggers have a limit to storage, and more points per second means storage fills faster The memory can be filled and stop recording, or better, the memory can over-write the earliest data  If a major storm passes, the data may be downloaded shortly thereafter Dataloggers write and store data in a compressed format that is often proprietary A proprietary program is then used to export the data on a serial link as a text file that can later be interpreted by other programs, like MS Excel 060212

27. 12.0.5.2.1 Serial Data Stream at 9600 bps Roberts Hall Data ID Year DOY HHMM Speed Gust Drct Solar Temp Rain test PV_V Ipv Iwt Pwt 24VBat Ibat 12VBat Relay Clip CMIN CMAX 24Min 24Max 24Sd EST mph mph deg W/m2 degC inch mV V A A W V A V 0_26 V V V V V V --------------------------------------------------------------------------------------------------------------------------------------------- [ID Year DOY HHMM Speed Gust Drct Solar Temp Rain] 103 2006 43 1449 11.63 14.94 290.8 796 12.01 0 13.59 43.79 8.69.889 24.68 27.77 -.185 13.73 27.43 5.004 6.593 4.971 27.68 27.81.026 103 2006 43 1450 11.42 14.94 294.9 753 12.12 0 13.52 43.64 -6999.881 24.36 27.66 -.651 13.68 27.34 4.978 4.992 4.971 26.64 27.73.14 103 2006 43 1451 17.86 29.25 301.2 464.4 12.16 0 13.39 46.19 3.39 19.02 581.6 27.46 -3.561 13.58 27.12 4.977 4.986 4.971 25.27 32.36 2.018 Latest observations from Roberts Hall Roof (~102 ft) Time (UTC) Wind Speed (mph) Windgust (mph) Wind Direction (deg) Temp. (deg F) Precip* (mm) Turbine Power (watts) PV Power (watts) Solar Radiation (w/m^2) 20:0012.914.9286.2530.3423208.78676.9 19:4518.425.7291.7530.3425239.91756.0

28. 12.0.5.3 Wind Statistics and Assessment Once the data are in the processing format, they must be screened to detect missing or bad data to prevent contamination of the results These series strings of data may then be processed to determine key statistics:  Highest speeds, averages, medians, modes, histograms, exceedance curves, etc. 050215

29. 12.0.5.4 Statistical Exceedance Curves Accumulated data can be sorted by value to gain an understanding of the statistical distribution  No distribution must be assumed --- known as nonparametric statistics Compute the percentile exceeded for each value and plot the values vs. the percentiles from 0% to 100% Determine the minimum, maximum, median, 10%- tile, and 90%-tile values A Weibull curve may be fit to the data to suggest a distribution 100218 Enlarged Plot follows

30. 12.0.5.4.1 Statistical Exceedance Curves 080212

31. 12.0.6.2 Sample of Roberts Hall Seabreeze Winds 040216

32. 12.0.6.3 Roberts Hall: 13 Days of Winds 030903 040216

33. 12.0.6.4 Predominant Wind Energy Direction Determines the Site Selected The energy rose is the cube of the wind speed (flower-like) rose In Palm Bay, Florida, this one- day wind data sample shows the main wind direction at 150 degrees azimuth An FPL WindLogics report shows Ft. Pierce FL annual estimates for 80 meters Several years of data are averaged to get a useful sample; 30 years desirable In obstructed areas, the site selection is critical to obtain the maximum wind energy N S 090805http://www.fpl.com/news/pdf/Windlogics_Results.pdf

34. 12.0 Conclusion: Wind Resources 1 Wind resources vary greatly with latitude, season, and surrounding terrain Extensive data and wind maps exist for wind prospecting At the mesoscale level, topographic information is being used to create predictions of wind speed from scattered real data Anemometers can be erected to obtain wind speeds in a likely locale for comparison to NWS long-term records An alternative is to erect a small wind turbine to sample the energy and help determine where a large turbine should be placed Wind resources may be excellent, but there is much more to installing a turbine 050215

35. Olin Engineering Complex 4.7 kW Solar PV Roof Array 080116 Questions?

36. References: Books Brower, Michael. Cool Energy. Cambridge MA: The MIT Press, 1992. 0-262-02349-0, TJ807.9.U6B76, 333.79’4’0973. Gipe, Paul. Wind Energy for Home & Business. White River Junction, VT: Chelsea Green Pub. Co., 1993. 0-930031-64-4, TJ820.G57, 621.4’5 Patel, Mukund R. Wind and Solar Power Systems. Boca Raton: CRC Press, 1999, 351 pp. ISBN 0-8493-1605-7, TK1541.P38 1999, 621.31’2136 Sørensen, Bent. Renewable Energy, Second Edition. San Diego: Academic Press, 2000, 911 pp. ISBN 0-12-656152-4. 030219

37. References: Websites, etc. http://www.idwr.state.id.us/energy/wind/wind_speed_map.pdf http://www.windpower.org/index.htm awea-windnet@yahoogroups.com. Wind Energy elist awea-wind-home@yahoogroups.com. Wind energy home powersite elist geothermal.marin.org/ on geothermal energy mailto:energyresources@egroups.com rredc.nrel.gov/wind/pubs/atlas/maps/chap2/2-01m.html PNNL wind energy map of CONUS windenergyexperimenter@yahoogroups.com. Elist for wind energy experimenters www.dieoff.org. Site devoted to the decline of energy and effects upon population www.ferc.gov/ Federal Energy Regulatory Commission www.hawaii.gov/dbedt/ert/otec_hi.html#anchor349152 on OTEC systems telosnet.com/wind/20th.html www.google.com/search?q=%22renewable+energy+course%22 solstice.crest.org/ dataweb.usbr.gov/html/powerplant_selection.html www.homepower.com/files/windsiteanalysis.pdf 060212

38. Slide stockpile follows! Older slides follow this one. Look at these if you have interest or time. It’s difficult to decide what to leave out of the lecture to save time!