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Remote Sensing in Wind Energy

Remote Sensing in Wind Energy. General. Used for wind farms In-flow angle Turbulence Wind speeds and directions Result: Optimal location and design for wind farms Turbines at maximum efficiency. Meteorological Towers. Why Remote Sensing?. Cheaper Low power requirements

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Remote Sensing in Wind Energy

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  1. Remote Sensing in Wind Energy

  2. General • Used for wind farms • In-flow angle • Turbulence • Wind speeds and directions • Result: • Optimal location and design for wind farms • Turbines at maximum efficiency

  3. Meteorological Towers

  4. Why Remote Sensing? • Cheaper • Low power requirements • Allows for solar energy • Less maintenance time

  5. SODAR • Measures by reflected self-emitted pulses • Detects • Pitch • Frequency • Sound reflected from turbulence

  6. LiDAR • Records data based on laser reflection • 3D Coherent Doppler LiDAR • Flexible • Different type of measurements • Conical • Vertical Slice • Fixed beam

  7. LiDAR • Can measure wind speeds with much higher accuracy than a MET tower • Linear regression coefficients are as high as 0.99

  8. Work Cited • http://www.ophir.com/overview--atmospheric-remote-sensing/ • http://asprs.org/a/publications/pers/2003journal/june/2003_jun_695-704.pdf • http://en.wikipedia.org/wiki/Precision_agriculture • http://www.asdi.com/applications/remote-sensing/airborne-remote-sensing • http://www.spectir.com/applications/geologic-airborne-hyperspectral/ • http://www.ars.usda.gov/is/AR/archive/mar05/remote0305.htm

  9. How? Why? Climate in the Atmosphere Climate uses both geostationary and polar orbiting satellites Affords us a view that we would otherwise be incapable of reaching without physically being at the given location. Evelyn Myers

  10. “We highlight some important discoveries about the climate system that have not been detected by climate models and conventional observations; for example, the spatial pattern of sea-level rise and the cooling effects of increased stratospheric aerosols”

  11. Some Satellites METSAT India GOES Geostationary USA Evelyn Myers

  12. Evelyn Myers Evelyn Myers Evelyn Myers

  13. Evelyn Myers

  14. Evelyn Myers

  15. In final

  16. Time lapse of climate occurrence Evelyn Myers

  17. http://www.eo-miners.eu/earth_observation/eo_eof_msa_remote_sensing_apps.htmhttp://www.eo-miners.eu/earth_observation/eo_eof_msa_remote_sensing_apps.htm Referances http://www.nersc.no/ http://www.eurac.edu/en/research/institutes/remotesensing/default.html http://0-onlinelibrary.wiley.com.opac.library.csupomona.edu/doi/10.1002/met.288/pdf https://www.google.com/search?q=remote+sensing+and+climate+change&source=lnms&sa=X&ei=8OwUU_vtGcryoASB2IK4CA&ved=0CAgQ_AUoAA&biw=1920&bih=1105&dpr=1 http://www.srh.noaa.gov/jetstream/remote/satellite.htm http://0-onlinelibrary.wiley.com.opac.library.csupomona.edu/doi/10.1002/met.288/pdf http://noaasis.noaa.gov/NOAASIS/ml/genlsatl.html http://www.goes.noaa.gov/ http://www.srh.noaa.gov/jetstream/remote/satellite.htm

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