wind lidar measurement optimization in complex terrain
DESCRIPTION
Wind Lidar measurement optimization in complex terrain. Matthieu Boquet , Laurent Sauvage, Rémy Parmentier, Jean-Pierre Cariou - LEOSPHERE/NRG Ferhat Bingöl – Risø DTU Dimitri Foussekis – CRES Armand Albergel – Aria Technologies Guillaume Dupont – Meteodyn - PowerPoint PPT PresentationTRANSCRIPT
Thursday. 22 April 2010
Wind Lidar measurement optimizationin complex terrain
Matthieu Boquet, Laurent Sauvage, Rémy Parmentier, Jean-Pierre Cariou - LEOSPHERE/NRGFerhat Bingöl – Risø DTUDimitri Foussekis – CRES
Armand Albergel – Aria TechnologiesGuillaume Dupont – MeteodynCatherine Meissner – WindSim
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Agenda
Introduction: complex terrain requirementsWind Lidar volume measurement vs. cups point measurement: assumptions for direct comparison and validity of these assumptionsCFD modeling and WindCube measurement process simulationGeometrical optimization and CFD combination for improving Lidar measurement in complex terrainsConclusions
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Wind Resource Assessment Program
Estimate the wind speed distribution:On-site measurement: masts and remote sensorsMeteorological stations and airports recordsFlow modeling software to extend measurements both in space (hub height and turbines location) and time (long-term scaling)
In complex terrain:Requires more on-site measurement locations to gain certainty in the WS estimation
A remote sensor is a precious complementary system:
But performances need to reach cup standards, i.e. bias<2%
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Pulsed Wind Lidar principleHOW AND HOW WELL DOES THE WINDCUBETM RETRIEVE WIND VELOCITY VERTICAL PROFILES?
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+10m
-10m
Lidar volume measurement principle
1) Pulse length and beam width
2) Conically scanning Probed volumes are
away one from another
3) Sequentially scanning
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Radial velocities measurement
v
vrad = v.axisbeam
qLaser shooting direction
aerosols
vrad
Radial velocity is the projection of aerosols velocity on laser beam axisFlow homogeneity assumption: aerosols velocity is the same at every radial velocity measurement locationU, V and W can be resolved
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Flat Moderately complex Mountainous
Terrain complexity influence
Lidar + mast
Forest
Terrain slope 10°
Wind direction
South-East:
Plateau, no trees
North-West:
10° slope, trees
At 80m Slope = 1.024
Slope = 0.988
Intercomparison of Horizontal wind speed at 78mN±40deg
y = 0.9627x - 0.2066R2 = 0.9911
y = 0.9457xR2 = 0.9907
0
4
8
12
16
20
0 4 8 12 16 20Cup Anemometer [m/s]
Win
dcub
e Li
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[m/s
]
At Risø test site Høvsøre
(onshore 1st phase of Norsewind Project)
Observed relative
difference:~1%
Observed relative
difference:~2%
Observed relative
difference:~6%
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CFD Modeling analysisUSING A CFD MODELING TO BETTER UNDERSTAND THE LIDAR AND ANEMOMETER DIFFERENCES IN COMPLEX TERRAIN
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Complex Spanish site
North-West wind
MERCURE/Aria TechnologiesCFD model adapted to complex topographyStationary CFD: A study of Lidar wind velocity retrieval process under various distorted flow conditionsSimulation of Lidar measurement process with MatLab
Met mast
WindCube
North-West wind
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Lidar vs. cup simulation
Lidar overestimation >5%
Lidar underestimation <-5%
North-West Wind
Terrain elevation represented with colorsBlack stars: locations of Lidar and cup measurement simulation
CFD simulation On site measurement
-5.8% -6.1%
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Horizontal gradient of vertical wind speed dependency
Lidar-cup relative difference vs. horizontal gradient of the horizontal wind speed No dependency
Lidar-cup relative difference vs. horizontal gradient of the vertical wind speed Clearly correlated
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Geometrical OptimisationHOW CAN WE MODIFY THE LIDAR MEASUREMENT PROCESS TO GET CLOSER TO CUP?
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Reducing the scanning cone ?
Probing a smaller volume then more homogeneous ? No! At a given height, difference depends only on
horizontal gradient of vertical wind speed
No magical scanning cone angleDangerous below 15° and above 30°
U UUW1 W2 W3
Radial vel.
Radial vel.Source of Bias
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30° vs. 15° - CRES data
Intercomparison of Horizontal wind speed at 78mN±40deg
y = 0.9627x - 0.2066R2 = 0.9911
y = 0.9457xR2 = 0.9907
0
4
8
12
16
20
0 4 8 12 16 20Cup Anemometer [m/s]
Win
dcub
e Li
dar
[m/s
]
Intercomparison of Horizontal wind speed at 78mN±40deg
y = 0.9457xR2 = 0.9871
0
4
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12
16
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0 4 8 12 16 20Cup Anemometer [m/s]
Win
dcub
e Li
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[m/s
]
30° cone angle 15° cone angle
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Adding more lines of sight ?
Consider first order variation of wind speedAs new unknown variables are introduced, one should add new Lidar equations to retrieve themHowever, a line of sight LOSi gives the radial velocity Si:
No LOS brings info on Wi
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Lidar-CFD combinationCOULD A CFD MODEL BRING THE MISSING INFO?
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Using a model to correct Lidar data
Model can provide the essential site specific info on the vertical wind speed distribution to correct Lidar data
Modeling
Relative difference on site Relative difference with corrected Lidar
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Methodology validation
Meteodyn WT and WindSim correction add-on tested on 2EN and CRES WindCubes on complex Greek site
CFD combination gets the bias from 6% down to 1%
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Conclusion
Point and volume measurement leads to wind speed value differences in complex terrainVertical wind speed loss of homogeneity is the main source of errorScanning cone angles between 15°-30° act similarly for horizontal wind speedMore lines of sight are not more useful infoMeteodyn WT and WindSim add-on:
WINDCUBE® Lidars data are now quantitatively useable on all types of
terrain
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