Pichugina

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Published on February 14, 2008

Author: Bianca

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Slide1:  14 th Coherent Laser Radar Conference Y. L. Pichugina1, 2, R. M. Banta2, N. D. Kelley3, B. J. Jonkman3, W. A. Brewer2, S. P. Sandberg2, and J. L. Machol1, 2 1 Cooperative Institute for Research in Environmental Sciences (CIRES), Boulder, CO 2 Earth System Research Laboratory, National Oceanic and Atmospheric Administration (ESRL/ NOAA), Boulder, CO 3National Wind Technology Center/National Renewable Energy Laboratory (NWTC/NREL) Golden, CO Advantage of the High Resolution Doppler Lidar measurements for nighttime boundary layer study and wind-energy applications Slide2:  14 th Coherent Laser Radar Conference Background The 2 mm High Resolution Doppler Lidar (HRDL) of NOAA/ESRL can be an important wind-measurement tool for wind energy applications. During the Lamar Low-Level Jet Project (LLLJP), nighttime observations were taken by HRDL to obtain detailed information about the periodic fluctuations or coherent turbulent structures in the wind flow at the rotor heights. The project was carried out during the first two weeks of September 2003 at a site south of Lamar, Colorado which is now a “wind farm” with more than 100 wind turbines. Slide3:  14 th Coherent Laser Radar Conference Presentation Objectives To summarize results of wind measurements obtained by HRDL during the Lamar Low Level Jet Program To demonstrate the ability of the HRDL measurements to provide accurate knowledge of wind and turbulence characteristics at the heights of turbine rotors and above. To present the results of a simultaneous inter-comparison of wind fields measured by two remote sensing technologies and direct tower-based measurements. Slide4:  14 th Coherent Laser Radar Conference Instrumentation Slide5:  14 th Coherent Laser Radar Conference HRDL measurements Vertical-slice (RHI) scans Conical (PPI) scans Fixed-beam scans Slide6:  14 th Coherent Laser Radar Conference Available products to monitor flow- examples Vertical profiles of UH and σU2 Mean wind speed and direction On regions such as US Great Plains, wind energy resource comes from a nocturnal LLJ Slide7:  14 th Coherent Laser Radar Conference HRDL-sonic anemometers data comparison bias: 0.96 ± 0.19 m s-1 slope: 1.017 ± 0.001 R2 = 0.96 N. Kelley et al.“Comparing Pulsed Doppler Lidar with Sodar and direct measurements for wind assessment” Presented at AWEA’s 2007 WindPower conference. Los Angeles, CA, 06/2007 Slide8:  14 th Coherent Laser Radar Conference HRDL-sodar data comparison Profiles from HRDL are deeper than from sodar “A confidence factor is determined by: consistency of the individual results from each of the 10 transmitted frequencies returned signal strength level of consistency between vertical layers (range gates). “ bias: −1.06 ± 0.19 m s-1 slope: 1.07 ± 0.01 R2 = 0.92 Slide9:  14 th Coherent Laser Radar Conference LLJ maximum serves as an upper bound to the layer of strong turbulence. Relation between HRDL streamwise velocity variance and LLJ wind speed maxima Shear created turbulence calculated from HRDL fixed-beam scan and tower-measured coherent turbulence kinetic energy (CTKE), which is based on momentum fluxes Slide10:  14 th Coherent Laser Radar Conference Power law wind speed profile U2=U1(z2/z1)α Slide11:  14 th Coherent Laser Radar Conference Summary Accurate estimates of wind resource potential and turbulence structure of the boundary layer at the heights of turbine rotors is very important as the height reached by commercial wind turbines increases up to 200-250 m to take advantage of stronger wind speeds at higher altitudes. The high temporal and spatial resolution of the HRDL data allows investigation of wind and turbulence conditions of the stable boundary layer, including the atmospheric layer occupied by wind-turbine rotors, in finer detail. Quantities of interest that can be easily monitored using Doppler lidar include -wind speed and direction profiles -nighttime evolution of the LLJ properties -role of the LLJ in generating turbulence below the jet -estimates of TKE profiles. The LLJ maximum serves as an upper bound to the layer of strong turbulence. Staring mode may be most useful real-time for wind energy applications Slide12:  14 th Coherent Laser Radar Conference Acknowledgements Field data acquisition and much of the analysis for this research were funded by the National Renewable Energy Research Laboratory (NREL) of the U.S. Department of Energy (DOE) under Interagency Agreement DOE-AI36-03GO13094. We thank our colleagues from ESRL: R. Alvarez, L. Darby, J.George, J. Keane, B. McCarty, A. Muschinski, R.Richter, A. Weickmann, and following from NREL: J. Adams, Dave Jager, Mari Shirazi and S. Wilde. We also wish to acknowledge NOAA Equal Opportunity Department for a financial support of our participation in this conference. THANK YOU! Slide13:  14 th Coherent Laser Radar Conference EXTRAS Obtaining Streamwise LIDAR Wind Profiles Using Vertical Scan Mode Data:  Obtaining Streamwise LIDAR Wind Profiles Using Vertical Scan Mode Data By design the majority of available data was collected in this mode Not optimal for obtaining streamwise velocity variance due to a potential lack of horizontal homogeneity at low angles sparse spatial sampling at high angles Stationary Stare Mode Geometry for Optimal LIDAR-Sonic Inter-comparison:  Stationary Stare Mode Geometry for Optimal LIDAR-Sonic Inter-comparison 31o Wind Flow LIDAR 30-m range gates 6 & 7 plan view elevation view UH Uradial N. Kelley et al. Presented at AWEA’s 2007 WindPower conference. Los Angeles, CA, June3-6 2007 Results of HRDL fixed beam and sonic anemometers comparison under optimal observing conditions:  Results of HRDL fixed beam and sonic anemometers comparison under optimal observing conditions Sonic UH full vector velocity is projected on to the LIDAR UH value for comparison over nominal periods of 10 minutes The two compare nominally within 0.2 ± 0.3 m/s or ± 2.5% over the observed velocity range of 1.0 to 11.3 m/s Compares favorably with similar measurements by Hall, et al using a much earlier version of the LIDAR at an elevation of 300 m and an observed velocity range of 1 to 22 m/s #Hall, et al, 1984, “Wind measurement accuracy of the NOAA pulse infrared Doppler LIDAR.” Applied Optics, 23, No. 15. N. Kelley et al. Presented at AWEA’s 2007 WindPower conference. Los Angeles, CA, June3-6 2007 Tower, SODAR, LIDAR inter-comparison results:  Tower, SODAR, LIDAR inter-comparison results LIDAR Vertical-Scan UH Referenced To All Tower Sonics UH LIDAR Vertical-Scan UH Referenced To SODAR UH Large bias, -1.02 ± 0.16 m/s LIDAR lower at all wind speeds Small slope error, 1.023 ± 0.010 1s variation, 0.89 m/s R2 = 0.918 Large bias, -1.35 ± 0.12 m/s LIDAR lower at all wind speeds Small slope error, 0.984 ± 0.011 1s variation, 0.67 m/s R2 = 0.955 N. Kelley et al. Presented at AWEA’s 2007 WindPower conference. Los Angeles, CA, June3-6 2007 Slide18:  14 th Coherent Laser Radar Conference Instrument Positions Slide19:  14 th Coherent Laser Radar Conference 120-m Tower & Sonic Anemometry ATI SAT/3K 3-axis sonic anemometers (7 Hz bandwidth, 0.05 sec time resolution) Mounted on support arms specifically engineered to damp out vibrations below 10 Hz Mounted 5 m from edge of 1-m wide, torsionally-stiff, triangular tower Arms orientated towards 300 degrees w.r.t. true north Slide20:  14 th Coherent Laser Radar Conference Scintec MFAS Phased Array SODAR Observed winds between 50 and 500 m 20-min averaging period 10-m vertical resolution Horizontal winds from 8 tilted beams and 10 frequencies over range of 1816-2742 Hz Variable pulse lengths Automatic gain control Very quiet site Slide21:  14 th Coherent Laser Radar Conference LLJ maximum serves as an upper bound to the layer of strong turbulence. Relation between HRDL streamwise velocity variance and LLJ wind speed maxima Shear created turbulence calculated from HRDL fixed-beam scan and tower-measured coherent turbulence kinetic energy (CTKE), which is based on momentum fluxes CTKE=1/2[(u’w’)2+(u’v’)2+(v’w’)2]1/2

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