comprehensive utilization of mesoscale modelling for wind energy applications
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Comprehensive utilization of mesoscale modelling for wind energy applications
Jake Badger, Andrea Hahmann, Xiaoli Guo Larsen, Alfredo Peña Diaz, Ekaterina Batchvarova, Sven-Erik Gryning, Rogier Floors, Hans Ejsing Jørgensen
Wind Energy DivisionRisø DTU
Risø DTU, Technical University of Denmark
Introduction Comprehensive adj Oxford English Dictionary
1. complete; including all, or nearly all elements, aspects etc.2. of or relating to understanding 3. ...
Comprehensive (1st meaning: complete)1. Wind resource assessment Poster ID 1562. Wind power forecasting Poster ID 1533. Extreme wind climate assessment Talk4. Mesoscale variability of wind Talk5. ‘Tall’ wind profiles Talk6. Flow over forest Talk 7. Wind power integration8. Wind farm wakes: their impacts on climate9. Wind turbine icing forecasting and climate10.Wind and wave climate studies11....
PREDICTABILITY OF WIND CONDITIONS17/3/2011, 11:00 - 12:30
SITING CHALLENGES16/3/2011, 11:00 - 12:30
Risø DTU, Technical University of Denmark
Introduction
Comprehensive (2nd meaning: understanding)
There is a need to understand• limitations of mesoscale modelling• appropriate use of the modelling results
Need valid link between mesoscale modelling results and measurement
This allows: • application• verification
We can also verify against other meteorological quantities (not just wind) to:
• test performance of model• indicate new linkages between mesocale modelling, microscale modelling and
measurements
Risø DTU, Technical University of Denmark
micro local corrections
local roughness corrections
mes
osca
le m
odel
out
put
estim
ates
of
site
con
ditio
ns
Routes from mesoscale model to site
Meso ‘local’ corrections
Risø DTU, Technical University of Denmark
micro local corrections
local roughness corrections
mes
osca
le m
odel
out
put
estim
ates
of
site
con
ditio
ns
Meso ‘local’ corrections
direct
Routes from mesoscale model to site
Risø DTU, Technical University of Denmark
micro local corrections
local roughness corrections
mes
osca
le m
odel
out
put
estim
ates
of
site
con
ditio
ns
Meso ‘local’ corrections
direct micro corrections only
Routes from mesoscale model to site
Risø DTU, Technical University of Denmark
micro local corrections
local roughness corrections
mes
osca
le m
odel
out
put
estim
ates
of
site
con
ditio
ns
Meso ‘local’ corrections
direct micro corrections only meso & micro corrections
Routes from mesoscale model to site
Risø DTU, Technical University of Denmark
u*, L or u(z) or u(zj)
h, z0
u at site
account for ‘local’ mesoscale effects
Evaluate u for standard heights above flat terrain of standard roughness lengths
account for ‘local’ microscale effects at site
WAsP WAsP Engineering
Mesocale model fields and output
Post-processing
Generalization
Badger et al (2010)
Application
Links in the model chain
corrections for• orography• roughness
application of• M-O similarity
theory• geostrophic drag
law
Risø DTU, Technical University of Denmark
Microscale local corrections
Mesoscale ‘local’ corrections
Site in northern Spain
due to orographymax +18%min +4%
due to orographymax +60%min +10%
due to roughnessmax +1%min - 6%
due to roughnessmax 0%min - 6%
Risø DTU, Technical University of Denmark
Verification of mean wind speed
meso & micro corrections
u* Lmeso u* Luser u(z) u(zj)
Site in northern Spain
Mesoscale ‘local’ corrections and microscale local corrections give best agreement with measurements
norm
aliz
ed w
ind
spee
d
direct micro corrections only
method
Risø DTU, Technical University of Denmark
Verification of mean power density
meso & micro corrections
u* Lmeso u* Luser u(z) u(zj)
Site in northern Spain
Mesoscale ‘local’ corrections and microscale local corrections give best agreement with measurements
norm
aliz
ed p
ower
den
sity
method
direct micro corrections only
Risø DTU, Technical University of Denmark
Importance of microscale... a motivation
Wind resource (power density) at 50 m calculated at different resolutions
10 km 5 km
2.5 km 0.1 km
50 km
50 km
324 W/m2
378 W/m2
328 W/m2
378 W/m2
323 W/m2
378 W/m2
505 W/m2
641 W/m2
mean power density of total area mean power density for windiest 50% of area
Risø DTU, Technical University of Denmark
Application at high resolution
Extreme wind climate
WAsP Engineering
Wind climate
WAsP
Risø DTU, Technical University of Denmark
New modes of model verification
100 m
600 m
Pulsed LIDAR wind measurement to 600 m
Floors et al (2010)
100 m
• Separate error contribution into mesoscale and microscale parts?• Microscale influence tending to reduce with height.
Risø DTU, Technical University of Denmark
New modes of model verification
1/L, WRF v sonic
Comparison of surface layer fluxes from sonics
Peña and Hahmann (2011)
heat flux, WRF v sonicu*, WRF v sonic
• Learn characteristic errors in surface fluxes.• B-L schemes may give unexpected velocity profiles.• Surface fluxes and theory for alternative profiles.
Risø DTU, Technical University of Denmark
• Modelling profiles beyond the surface layer
After Gryning et al (2007), 3 characteristic lengths scales used to define boundary-layer profiles:
Neutral with baroclinicity term (Kelly 2011, pers.comm.) (stable and unstable profiles have corresponding
expressions)
Advancing the links in the model chain
Gryning et al 2007
Risø DTU, Technical University of Denmark
Advancing the links in the model chain
Peña et al (2010)
Hahmann 2011
• Modelling profiles beyond the surface layer
After Gryning et al (2007), 3 characteristic lengths scales used to define boundary-layer profiles:
Neutral with baroclinicity term (Kelly 2011, pers.comm.) (stable and unstable profiles have corresponding
expressions)
B-L height from pulsed LIDARvia aerosols’ backscatter
Julian dayz
[m]
B-L height from WRF
time of day (LST)
B-L
hei
ght
[m]
Risø DTU, Technical University of Denmark
Kelly and Gryning (2010) describe method to correct long-term profile according to long-term distribution of stability (pdf of 1/L).
Peña and Hahmann (2011) use WRF to evaluate long-term distribution of stability (pdf of 1/L) and thus give a long-term stability correction < >
Advancing the links in the model chain
Peña and Hahmann (2011)
< > at 70 m
• Correction of long-term profile will be useful in application of generalized wind climates at sites.
Risø DTU, Technical University of Denmark
• Verification of mesoscale modelling applications in wind energy requires consideration of local unresolved effects.
• Valuable new model verification possible via application of new measurement technologies.
• New theory gives possibilities for advancing the mesoscale to microscale model chain.
• Understanding mesoscale model characteristics guides appropriate use of mesoscale model output:
• boundary layer parameterizations• surface layer and boundary layer properties
• Most appropriate use may not always be the most obvious.
• Verification is an essential part of model development loop.
Summary and conclusions
Risø DTU, Technical University of Denmark
Thank you for your attention
jaba@risoe.dtu.dk
Oral presentation sessions
PREDICTABILITY OF WIND CONDITIONS17/3/2011, 11:00 - 12:30
SITING CHALLENGES16/3/2011, 11:00 - 12:30
Poster session
Poster ID 156 on uncertainty mapping
Poster ID 153 on forecasting
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