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Harris M., Locker I., Douglas N., Girault R., Abiven C., and Brady O. (2010) Validated adjustment of remote sensing bias in complex terrain using CFD. European Wind Energy Conf., Warsaw Jelalian A. V. (1992) Laser radar systems, Artech House, Boston Karlsson C. J., Olsson F. A., Letalick D., and Harris M. (2000) All-fiber multifunction CW 1.55 micron coherent laser radar for range, speed, vibration and wind measurements. Appl. Opt. 39:3716–3726 Kristensen L. (1999) The perennial cup anemometer. Wind Energy 2:59–75 Kragh K. A., and Hansen M. H (2011) Individual Pitch Control Based on Local and Upstream Inflow Measurements. Proceedings of 49th AIAA Aerospace Sciences, American Institute of Aeronautics and Astronautics, AIAA 2011–813, Orlando, Florida Kragh K. A., Hansen M. H, and Mikkelsen T. (2013) Precision and shortcomings of yaw error estimation using spinner-based light detection and ranging. Wind Energy 16:353–366 Lading L., Hanson S., and Skov Jensen A. (1984) Diffraction-limited lidars: the impact of refractive turbulence. Appl. Opt. 23:2492-2497 Laks J., Pao L. Y., Simley E., Wright A., Kelley N., and Jonkman B. (2011) Model Predictive Control Using Preview Measurements From LIDAR. Proceedings of 49th AIAA Aerospace Sciences, American Institute of Aeronautics and Astronautics, AIAA 2011–813, Orlando, Florida. Loudon R. (2000) The quantum theory of light, Oxford University Press, 3rd edition Mikkelsen T., Hansen K., Angelou N., Sjöholm M., Harris M., Hadley P., Scullion R., Ellis G., and Vives G. (2010) Lidar wind speed measurements from a rotating spinner. European Wind Energy Conf., Warsaw Pearson G. N., Roberts P. J., Eacock J. R., and Harris M (2002) Analysis of the performance of a coherent pulsed fiber lidar for aerosol backscatter applications. Appl. Opt. 41:6442-6450 Pedersen A. T., Montes B. F., Pedersen J. E., Harris M., and Mikkelsen T. (2012) Demonstration of shortrange wind lidar in a high-performance wind tunnel, EWEA conference PO78, Copenhagen Peña A., Hasager C. B., Gryning S.-E., Courtney M., Antoniou I., Mikkelsen T. (2009) Offshore wind profiling using light detection and ranging measurements. Wind Energy 12:105-124 Pitter M., Abiven C., Harris M., Barker W., and Brady O. (2012) Lidar and computational fluid dynamics for resource assessment in complex terrain. EWEA conference PO80, Copenhagen. Rogers T., Byme A., McCoy T., and Briggs K. (2012) Expected impacts on cost of energy through lidar based wind turbine control. EWEA 2012. A Rutherford A, M Harris M, W Barker W, E Burin de Roziers E., R Pitter M., R Scullion R., and C Slinger C. (2012) Lidar calibration and performance validation process. AWEA 2012, Atlanta. Schlipf D., and Kuhn M. (2008) Prospects of a collective pitch control by means of predictive disturbance compensation assisted by wind speed measurements. German Wind Energy Conference (DEWEK 2008), pp. 1–4 Schlipf D., Anger J., Kapp S., Bischoff O., Hofsäß M., Rettenmeier A., and Kühn M. (2011) Prospects of optimization of energy production by lidar assisted control of wind turbines Proceedings of European Wind Energy Conference and Exhibition, EWEA 2011. Siegman A. E. (1986) Lasers, University Science Books, Mill Valley Simley E., Pao L. Y., Frehlich R., Jonkman B., and Kelley N (2011) Analysis of Wind Speed Measurements using Continuous Wave LIDAR for Wind Turbine Control. Proceedings of 49th AIAA Aerospace Sciences, American Institute of Aeronautics and Astronautics, AIAA 2011-263, Orlando, Florida Slinger C., Leak M., Pitter M., and Harris M. (2013) Relative Power Curve Measurements Using Turbine Mounted, Continuous Wave Lidar. EWEA 2013. Smith D. A., Harris M., Coffey A. S., Mikkelsen T., Jørgensen H. E., and Mann J. (2006) Wind lidar evaluation at the Danish wind test site in Høvsøre. Wind Energy 9:87–93 Sonnenschein C.M.andHorriganF.A.(1971) Signal-to-noise relationships forcoaxialsystems thatheterodyne backscatter from the atmosphere. Appl. Opt. 10:1600–1604 Vaughan J. M. and Forrester P. A. (1989) Laser Doppler velocimetry applied to the measurement of local and global wind. Wind Eng. 13:1–15 Wagner R., Jørgensen H. E., Paulsen U. S., Larsen T. J., Antoniou I., and Thesbjerg L. (2008) Remote sensing used for power curves. IOP Conf. Series: Earth and Environ. Sci. 1:012059 102 <strong>DTU</strong> Wind Energy-E-Report-0029(EN)
Wagner R., Mikkelsen T., and Courtney M. (2009) Investigation of turbulence measurements with a continuous-wave conically scanning lidar. Risø-R-1682(EN), Roskilde S Wharton S., and Lundquist J. K. (2012) Atmospheric stability affects wind turbine power collection. Environmental Research Letters textbf7: 014005. Wiggins J. (2009) Unpublished internal report. Natural Power Zak J. A. (2003) Atmospheric boundary layer sensors for application in a wake vortex advisory system. NASA/CR-2003-212175 <strong>DTU</strong> Wind Energy-E-Report-0029(EN) 103
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Remote Sensing for Wind Energy DTU
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Author: Alfredo Peña, Charlotte B.
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4 Introduction to continuous-wave D
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8 Nacelle-based lidar systems 157 8
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12 Complex terrain and lidars 231 1
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1 Remote sensing of wind Torben Mik
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Figure 2: Calibration, laboratory w
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Figure 3: Example of scatter plots
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1.2.3 Summary of sodars Most of tod
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1.3.3 Wind lidars Measuring wind wi
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Figure 6: CW wind lidars (ZephIRs)
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Further developments Furthermore, n
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2 The atmospheric boundary layer S
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Figure 9: Large spatial scale varia
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Du3 Dt Du1 Dt Du2 Dt The three mome
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Figure 13: Consensus relations betw
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ψ z L ∼ − 5 L . For unstable c
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Figure 15: Behavior of the turbulen
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Figure 17: Newly developed models t
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The value of q0 at the surface is d
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the spray is the source of icing on
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u∗2 u∗1 u1(h) = u∗1 k ln h
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Figure 26:Land-seabreeze system,whe
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Figure28:Three dimensionalpicture o
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sufficient information. Finally, we
Page 51 and 52: Mann, J. (1998) Wind field simulati
Page 53 and 54: (2010) and comparison under differe
Page 55 and 56: To get the velocity field from the
Page 57 and 58: τ(k) [Arbitrary units] 10 3 10 2 1
Page 59 and 60: (Koopmans, 1974; Bendat and Piersol
Page 61 and 62: anemometer was installed at each en
Page 63 and 64: and fSw(f) u 2 ∗ = 1.05n 1+5.3n 5
Page 65 and 66: and n = 0.468. This spectrum implie
Page 67 and 68: to be calculated. We do that on a m
Page 69 and 70: Notation A Charnock constant neutra
Page 71 and 72: Maxey M. R. (1982) Distortion of tu
Page 73 and 74: 4.2 Basic principles of lidar opera
Page 75 and 76: 4.2.5 Wind profiling in conical sca
Page 77 and 78: 4.3.1 Behaviour of scattering parti
Page 79 and 80: the beam radius at the output lens.
Page 81 and 82: from which the value of VLOS is der
Page 83 and 84: the atmosphere. The SNR 4 for a win
Page 85 and 86: individual line-of-sight wind speed
Page 87 and 88: A general approach to mitigating th
Page 89 and 90: from ±VH sinδ (if the tilt is tow
Page 91 and 92: as a down draught (of the same abso
Page 93 and 94: Table 7: Combined results from 28 Z
Page 95 and 96: in Eastern Jutland between January
Page 97 and 98: Figure 56: Normalized power curves
Page 99 and 100: the concept. Developments include i
Page 101: References x horizontal position in
Page 105 and 106: 5.2 End-to-end description of pulse
Page 107 and 108: Scanner Coherent lidar measure the
Page 109 and 110: Figure 62: Radial wind velocity ret
Page 111 and 112: transform in order to use data obta
Page 113 and 114: This wavelength is also the most fa
Page 115 and 116: Eq.(132)isadaptedforcollimatedsyste
Page 117 and 118: 5.3.6 Existing systems and actual p
Page 119 and 120: (Gottshall et al., 2010; Albers et
Page 121 and 122: References Albers A., Janssen A. W.
Page 123 and 124: derived from fluctuations of the wi
Page 125 and 126: Acoustic received echo (ARE) method
Page 127 and 128: Figure 71: Sample time-height cross
Page 129 and 130: A gradient minimum is characterized
Page 131 and 132: Figure73:Bragg-relatedacoustic(belo
Page 133 and 134: stability (inversion strength) can
Page 135 and 136: Figure 76: Combined soundingwith a
Page 137 and 138: Figure 79: Favorite regions (shaded
Page 139 and 140: Direct detection of MLH from acoust
Page 141 and 142: Engelbart D.A.M.and Bange J. (2002)
Page 143 and 144: 7 What can remote sensing contribut
Page 145 and 146: uyms 9.0 8.5 8.0 7.5 7.0 120 140 16
Page 147 and 148: Bottom of rotor Φ rotation r w u
Page 149 and 150: Height Height Hub 1.6 1.4 1.2 1.0 0
Page 151 and 152: PP rated PP rated 1.0 0.8 0.6 0.4 0
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KEprofileKEhub 1.2 1.1 1.0 0.9 0.8
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PP rated WS Lidarms 1.0 0.8 0.6 0.4
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8 Nacelle-based lidar systems Andre
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• Flexibletrajectories.Dependingo
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Figure 104: Sketch of simultaneous
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The normal wind direction vector nw
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Figure 109: Test site at DTU Wind E
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Figure 112: Power curve met mast an
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Notation C number of sent photons C
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9 Lidars and wind turbine control -
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for three unknowns, it is impossibl
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model of the blade pitch actuator,
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|GRL| [-] 1 0.8 0.6 0.4 0.2 10 k [r
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PSD(Ωg) [(rpm) 2 /Hz] PSD(Ωg) [
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0.04 0.03 ˆk [ rad m ] 0.02 0.63 0
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[%] 10 0 −10 −20 −30 MyT Moop
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PSD(θ1) [rad 2 /Hz] PSD(Moop1) [Nm
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Pel/Pel,max [-] 1 0.98 0.96 0.94 0.
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fL weighting function GRL transfer
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E. Hau, Windkraftanlagen, 4th ed. S
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¨¦¦§©¡§ ¥§¨¦¦§£ ¡¥
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vertical (m) 150 100 50 R d 0
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With feedback only, on the other ha
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Figure 136: Estimated preview requi
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Normalized C r = C r P Q 2 W (r) b
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Normalized C r = C r P Q 2 W (r) b
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Coherence 1 0.8 0.6 0.4 0.2 0 10
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Coherence 1 0.8 0.6 0.4 0.2 0 10
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Magnitude Squared 10 8 10 7 10 6 10
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Figure 148: During simulation, FAST
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Figure 149: Collective flap respons
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Magnitude (abs) blade pitch gen spe
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• Measurement coherence, which ca
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Jonkman, B. (2009) TurbSim user’s
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11 Lidars and wind profiles Alfredo
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z [m] 160 100 80 60 40 20 10 15 20
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z [−] zo 1 κ ln 40 38 36 34 32 3
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z [m] z [m] 1000 900 800 700 600 50
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the growth of the length scale, agr
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12 Complex terrain and lidars Ferha
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Figure 158: The ZephIR models which
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Uconst wΑx l h Φ h.tanΦ Figure 1
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Figure 162: Lavrio: The scatter plo
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Figure 163: Panahaiko: The scatter
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References Albers A. and Janssen A.
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Wexler (1968), where the limitation
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13.2.1 Systematic turbulence errors
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where x is the center of the scanni
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The theoretical systematic errors a
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Height (m) 160 140 120 100 80 60 40
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Height (m) Height (m) 160 140 120 1
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RMSPE (%) 70 60 50 40 30 20 10 0 vu
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involves interaction of all compone
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Lindelöw P. (2007) Fibre Based Coh
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plications, including meteorologica
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Figure 173: Rayleigh-Jeans’ appro
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Figure 176: Brightness temperature
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with rain are shown in Fig. 179. A
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This method gives a good accuracy (
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Figure 183: A recent maintenance in
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Figure 185: Temperature profiles in
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References s point in space Sν(s)
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Also the Doppler Centroid anomaly c
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Christiansen et al., 2006). The res
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educe speckle noise, a random noise
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Figure 188: Envisat ASAR wind field
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Figure 190: Envisat ASAR wind field
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Satellites in sun-synchronous polar
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500 overlapping scenes for wind res
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(with the fewest samples). The unce
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Badger M., Hasager C. B., Thompson
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Ren Y. Z., Lehner S., Brusch S., Li
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tracking, climate studies, air-sea
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The modified logarithmic wind profi
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sea ice mask was applied and σ0 me
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QuikSCAT 25 20 15 10 5 Horns Rev Fi
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Figure 203:Example of an ASCAT coas
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References Bourassa M.A., Legler D.
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DTU Wind Energy Technical Universit
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