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LidarCupms WS Lidarms 25 20 15 10 5 1.0 0.5 0.0 "Lidar A" "Lidar B" y0.0770.991 x R 2 0.996 y0.998 x R 2 0.996 0 a 0 5 10 15 20 25 WS Cupms 0.5 1.0 0 5 10 15 c 20 25 Cupms LidarCupms WS Lidarms 25 20 15 10 5 1.0 0.5 0.0 y0.0220.992 x R 2 0.999 y0.990 x R 2 0.999 0 b 0 5 10 15 20 25 WS Cupms 0.5 1.0 0 5 10 15 d 20 25 Cupms Figure 99: (a and b) Linear regression of 10-min mean wind speeds measured by a lidar and a cup anemometer from two lidar systems; (c and d) lidar error for each system References Antoniou I. (2009) Wind shear and uncertainties in power curve measurement and wind resources. WindPower Elliot D. L. and Cadogan J. B. (1990) Effects of wind shear and turbulence on wind turbine power curve. Proc. of the European Community Wind Energy Conf., Madrid IEC (2005) IEC 61400-12-1 Wind turbines - Power performance measurements of electricity producing wind turbines. Int. Electrotechnical Commission Manwell J.F.,McGowanJ. G.,andRogers A. L.(2002) Windenergy explained: Theory, design andapplication, John Wiley & Sons Ltd, 577 pp Sumner J. and Masson C. (2006) Influence of atmospheric stability on wind turbine power performace curves. J. Solar Energy Eng. 128:531–538 Wagner R., Antoniou I., Pedersen S. M., Courtney M., and Jørgensen H. E. (2009) The influence of the wind speed profile on wind turbine performance measurements. Wind Energy 12:348–362 156 <strong>DTU</strong> Wind Energy-E-Report-0029(EN)
8 Nacelle-based lidar systems Andreas Rettenmeier, Jan Anger, Oliver Bischoff, Martin Hofsäss, David Schlipf and Ines Würth Stuttgart Chair of Wind Energy, Institute of Aircraft Design, Universität Stuttgart, Stuttgart, Germany 8.1 Summary The use of a nacelle-based lidar system allows measuring turbine inflow and wake in a very high spatial and temporal resolution. The new measurement techniques to be developed have direct applications on- and offshore for the verification of wake models, predictive control strategies and new methods for power curve determination and load estimation. An adaptive scanning device was developed for the standard pulsed lidar system Windcube. This additional system has been conceived with a certain flexibility to allow different trajectories and to scan horizontally the flow field in front and behind of turbines covering the whole rotor disc. The design and construction of the device was supported by a software tool for wind turbine lidar simulation. Based on the results of the simulation of different trajectories, requirements to the hardware and software adaptation could be defined. 8.2 Introduction Installation of the lidar system on the nacelle of a turbine is advantageous because in this way the lidar yaws with the turbine and the laser beam is always orientated along the up- or downwind wind direction, depending on the application. Ifthelidarsystem“islooking”upwindonecanmeasuretheincomingwindfore.g.predictive turbine control, loadestimationor powercurve determination.If the lidaris lookingdownwind it is possible to measure the turbine’s wake wind and thus making the validation of wake models possible. The wind speed component of the line-of-sight vector is much higher when operating horizontally from a nacelle than from the ground. The development of different nacelle-based lidar systems are on the one hand commercial products (e.g. Blue Scout, Avent) with two/three beam directions which mainly focus to support the yaw control of the turbine. On the other hands different research lidar were developed for nacelle applications. For this reason one of the first CW-lidars from QinetiQ was used for the first investigations regarding turbine control (Harris et al., 2006) and wake (Trujilloetal., 2008).AnotherCW-lidarwasmountedin therotatingspinnerofawindturbine (Mikkelsen et al., 2010). The lidar system presented here is based on the pulsed lidar device “Windcube” of Leosphere (Rettenmeier et al., 2010). 8.3 The units of the lidar scanner The SWE lidar system consists of two components. The first component is the commercial “Windcube WLS-7” from Leosphere. The second part of the used system is a scanner specifically created for nacelle-based lidar measurements. 8.3.1 Windcube The “Windcube WLS 7” was developed to measure wind speed and wind direction from the ground in order to replace the conventional met masts for wind potential analyses in some areas and to support the certification process regarding power curve and load measurements <strong>DTU</strong> Wind Energy-E-Report-0029(EN) 157
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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
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Mann, J. (1998) Wind field simulati
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(2010) and comparison under differe
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To get the velocity field from the
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τ(k) [Arbitrary units] 10 3 10 2 1
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(Koopmans, 1974; Bendat and Piersol
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anemometer was installed at each en
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and fSw(f) u 2 ∗ = 1.05n 1+5.3n 5
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and n = 0.468. This spectrum implie
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to be calculated. We do that on a m
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Notation A Charnock constant neutra
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Maxey M. R. (1982) Distortion of tu
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4.2 Basic principles of lidar opera
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4.2.5 Wind profiling in conical sca
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4.3.1 Behaviour of scattering parti
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the beam radius at the output lens.
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from which the value of VLOS is der
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the atmosphere. The SNR 4 for a win
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individual line-of-sight wind speed
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A general approach to mitigating th
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from ±VH sinδ (if the tilt is tow
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as a down draught (of the same abso
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Table 7: Combined results from 28 Z
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in Eastern Jutland between January
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Figure 56: Normalized power curves
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the concept. Developments include i
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References x horizontal position in
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Wagner R., Mikkelsen T., and Courtn
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
Page 153 and 154: KEprofileKEhub 1.2 1.1 1.0 0.9 0.8
Page 155: PP rated WS Lidarms 1.0 0.8 0.6 0.4
Page 159 and 160: • Flexibletrajectories.Dependingo
Page 161 and 162: Figure 104: Sketch of simultaneous
Page 163 and 164: The normal wind direction vector nw
Page 165 and 166: Figure 109: Test site at DTU Wind E
Page 167 and 168: Figure 112: Power curve met mast an
Page 169 and 170: Notation C number of sent photons C
Page 171 and 172: 9 Lidars and wind turbine control -
Page 173 and 174: for three unknowns, it is impossibl
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Page 177 and 178: |GRL| [-] 1 0.8 0.6 0.4 0.2 10 k [r
Page 179 and 180: PSD(Ωg) [(rpm) 2 /Hz] PSD(Ωg) [
Page 181 and 182: 0.04 0.03 ˆk [ rad m ] 0.02 0.63 0
Page 183 and 184: [%] 10 0 −10 −20 −30 MyT Moop
Page 185 and 186: PSD(θ1) [rad 2 /Hz] PSD(Moop1) [Nm
Page 187 and 188: Pel/Pel,max [-] 1 0.98 0.96 0.94 0.
Page 189 and 190: fL weighting function GRL transfer
Page 191 and 192: E. Hau, Windkraftanlagen, 4th ed. S
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Page 195 and 196: vertical (m) 150 100 50 R d 0
Page 197 and 198: With feedback only, on the other ha
Page 199 and 200: Figure 136: Estimated preview requi
Page 201 and 202: Normalized C r = C r P Q 2 W (r) b
Page 203 and 204: Normalized C r = C r P Q 2 W (r) b
Page 205 and 206: 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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