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UNCERTAINTY OF LIDARS IN COMPLEX TERRAIN. Klaus Vogstad, Anne H Simonsen, Kyle Brennan and John Amund Lund Vienna, 06.02.2013. Uncertainty of lidars in complex terrain. Project goal. Quantify uncertainty of Lidars in complex terrain - PowerPoint PPT Presentation
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UNCERTAINTY OF LIDARS IN COMPLEX TERRAINKlaus Vogstad, Anne H Simonsen,
Kyle Brennan and John Amund Lund
Vienna, 06.02.2013
UNCERTAINTY OF LIDARS IN COMPLEX TERRAIN
Virtual measure-ments
PROJECT GOAL
Uncertaintyproduction estimate [%]
25
20
15
10
Measure-ment masts
Combined Lidar and
Masts
295 kEUR100 kEUR2.7 kEUR
Cost of measurement campaign
Cost
efficiency
Quantify uncertainty of Lidars in complex terrainDetermine the most cost-effective configuration of measurement campaigns (cost vs quality)Test the usefullness of Lidars with variable scanning geometries
PROJECT PARTICIPANTS
SPONSORS
PROJECT OVERVIEW
TEST CAMPAIGN
WINDCUBE ZephIR GalionModel V1 300 Long RangeLidar type Pulse Continuous PulseRange (m) 40 – 200 10 – 200 40 – 4,000
Manufacturer Leosphere Zephir Limited Sgurr Energy
Consultant Deutsche Wind Guard Natural Power Sgurr Energy
Phase I – Blind test at 80m mast: 6 weeksPhase II – Blind test at 50m mast: 7 weeks
Parameters tested:• Wind speed• Wind direction• Turbulence • Uncertainties
Results with and without CFD correctionevaluated.
Wind data gradually released to Consultants (50, then 80m)
Overview of Lidar systems
50m mast
• Flow model solved using WindSim- Sector resolution 5 degree
- Wind speed above boundary layer 10 m/s
- Terrain based on 5m height contours (5x5m grid resolution)
• Evaluation of lidar derived velocity by evaluating Vlos for every beam
- Derived velocity compared to cone center velocity (or mast center) for comparison
- Velocity scaling factor derived for each wind speed
• Derived wind speed is used as reference for scaling of lidar data- Derived wind direction is used for
sectorwise scaling of data
CFD CORRECTION
Sectorwise correction factors phase I Sectorwise correction factors phase II
CFD CORRECTION• Scaling factors differ significantly from sector to sector
• Very complex terrain gives high dependency on boundary condition in flow model• Small changes in wind speed can lead to large changes in correction factors
• Smoothing is applied to results to avoid large oscillations in correction factor• Neutral flow stratification was assumed for all wind directions • Large dependency on orientation for 4-beam lidars
0 50 100 150 200 250 300 350
1.016
1.018
1.02
1.022
1.024
1.026
1.028
1.03
1.032
1.034
1.036
Sector [deg]
Corre
ction
facto
r [1]
0 50 100 150 200 250 300 350
1.01
1.015
1.02
1.025
1.03
1.035
1.04
1.045
1.05
1.055
Sectors [deg]
Corre
ction
facto
r [1]
5 10 15 20 25 30
5
10
15
20
25
30
Wind speed anemometer [m/s]
Win
d sp
eed
lidar
[m/s
]
VVCFD
V errorVCFD error
5 10 15 20 25 30-12
-10
-8
-6
-4
-2
0
2
4
6
8
Dev
iatio
n [%
]
PHASE 1 RESULTS – 80M – WINDCUBE LIDAR
Comparison of wind speed at 80m - WINDCUBE Lidar against mast M4703.6 weeks of data
5 10 15 20 25 30
5
10
15
20
25
30
Wind speed anemometer [m/s]
Win
d sp
eed
lidar
[m/s
]
VVCFD
V errorVCFD error
5 10 15 20 25 30-12
-10
-8
-6
-4
-2
0
2
4
6
8
Dev
iatio
n [%
]
Comparison of wind speed at 80m – Zephir 300 Lidar against mast M47036 weeks of data
PHASE 1 RESULTS – 80M – ZEPHIR LIDAR
5 10 15 20 25 30
5
10
15
20
25
30
Wind speed anemometer [m/s]
Win
d sp
eed
lidar
[m/s
]
VVCFD
V errorVCFD error
5 10 15 20 25 30-12
-10
-8
-6
-4
-2
0
2
4
6
8
Dev
iatio
n [%
]
Comparison of wind speed at 80m – Galion Long Range Lidar against mast M47036 weeks of data
PHASE 1 RESULTS – 80M – GALION LIDAR
5 10 15 20 25 30
5
10
15
20
25
30
Wind speed anemometer [m/s]
Win
d sp
eed
lidar
[m/s
]
VVCFD
V errorVCFD error
5 10 15 20 25 30-12
-10
-8
-6
-4
-2
0
2
4
6
8
Dev
iatio
n [%
]
Comparison of wind speed at 50m – WindCube v1 Lidar against mast M47047 weeks of data
PHASE 2 RESULTS – 80M – WINDCUBE LIDAR
5 10 15 20 25 30
5
10
15
20
25
30
Wind speed anemometer [m/s]
Win
d sp
eed
lidar
[m/s
]
VVCFD
V errorVCFD error
5 10 15 20 25 30-12
-10
-8
-6
-4
-2
0
2
4
6
8
Dev
iatio
n [%
]
Comparison of wind speed at 50m – Zephir 300 Lidar against mast M47047 weeks of data
PHASE 2 RESULTS – 80M – ZEPHIR LIDAR
5 10 15 20 25 30
5
10
15
20
25
30
Wind speed anemometer [m/s]
Win
d sp
eed
lidar
[m/s
]
VVCFD
V errorVCFD error
5 10 15 20 25 30-12
-10
-8
-6
-4
-2
0
2
4
6
8
Dev
iatio
n [%
]
Comparison of wind speed at 50m – Galion Long Range Arc Scan from 450m against mast M4704. 7 weeks of data
PHASE 2 RESULTS – 80M – GALION LIDAR
SUMMARY OF RESULTS
CONCLUSION1) Uncertainty of Lidars is comparable to cup anemometry (2.5% )
in complex terrain, if we allow for CFD correction 2) The Lidar use in complex terrain requires confidence in CFD
correction3) Data availability was low due to climatological conditions of the
site (low level clouds, low aerosols) and power supply problems4) All systems performed well, none were superior on all statistical
parameters5) From the experience of this campaign, we recommend use of
Lidars for measurement campaigns in complex terrain6) The most cost-effective measurement campaign is probably a
combination of one mast (for LTC) and one Lidar for spatial coverage