Title: Modelling Of Wind Speed and Turbulence Intensity For A Forested Site In Complex Terrain
1Modelling Of Wind Speed and Turbulence Intensity
For A Forested Site In Complex Terrain
- C. Montavon1, I. Jones1, D. Malins2,
- C. Strachan2, R. Spence3, R. Boddington3
1ANSYS UK Ltd, 2Scottish Power Renewables,
3SgurrEnergy Ltd
2Motivation
- More and more onshore sites developed in complex
terrain and complex forestry environment. - Associated risks
- Separation, negative shear exponent factors
- Increased turbulence
- ? implications for turbine longevity and energy
output - On such sites, standard industry tools
(linearised models) used outside of the envelope
where they are meant to operate - CFD models increasingly advocated to be better
suited for difficult sites. - Question is what can CFD deliver in terms of
accuracy? - ? need for validation
3Contents
- Part 1
- Harestanes site description
- Modelling assumptions
- Mast to mast cross predictions
- Wind speeds
- Turbulence intensity
- Part 2
- Comparisons with Galion LIDAR campaign
- Conclusions
- Acknowledgements
- Carbon Trust for providing funding to the POWFARM
project - Scottish Power Renewables for providing us with
their mast data, and allowing the deployment of
the Galion LIDAR on their site.
4Complex terrain
- Harestanes is situated in the Scottish Borders
- Developed by Scottish Power Renewables
- Site elevation between 50 and 700m
- Wind regimes predominantly from the south-west
and east/north east - Complex terrain but not very complex as only few
regions where slopes exceed critical slope for
separation
Wind rose at Holehouse Hill
5 but mostly complex forestry
Forestry cover in the proximity of the deployment
location for the Galion LIDAR ? Lots of forestry
coupes, each with its own tree height
6Modelling assumptions
- Simulations done with WindModeller (ANSYS CFD),
solving for - Transient RANS, SST turbulence model
- Atmospheric stability accounted for via equation
for potential temperature, buoyancy effect in
turbulence model - Lopes da Costa forestry model (variable tree
height, constant loss coefficient), background
roughness of 0.05m - details in paper
7Masts on site
- 4 masts on site, 3 near hill tops, 1 in a
location with difficult flow conditions (valley,
proximity to forestry) - Cross prediction done for 3 masts with long
concurrent time series
All masts with data at 70m, 60m, 40m, 30m Hill
top masts Holehouse Hill Hareshaw Rig Valley
mast Bran Rig
8Mast to Mast Cross Prediction (wind speed)
- Maximum relative errors in wind speed cross
predictions for three model configurations - Purely neutral
- Conventionally neutral i.e. stable conditions in
free stream, with potential temperature gradient
of US standard atmosphere, and neutral conditions
at ground (adiabatic).
3 masts (70m only) 3 masts (70m only) 3 masts (70m only) 3 masts (all heights) 3 masts (all heights) 3 masts (all heights)
Model BRAN-HOL BRAN-HAR HOL-HAR BRAN-HOL BRAN-HAR HOL-HAR
neutral 11.8 13.3 1.8 24.0 24.0 3.2
stable 0.4 4.1 5.4 2.9 6.5 6.2
9Shear exponent factor (40 to 60m) predictions
Purely neutral
Including freestream stability
Holehouse Hill
Bran Rig
Data red symbols and error bars (average
stdev) Model black symbols
10Relative wind speed between masts, normalised by
HOL 70m
Purely neutral
Including freestream stability
Holehouse Hill
Bran Rig
Data coloured symbols and error bars (average
stdev) Model black symbols
11Relative TI between masts at 70m, normalised by
HOL 70m
Purely neutral
Including freestream stability
Hareshaw Rig
Bran Rig
Data red symbols and error bars (average
stdev) Model black symbols
12Separation prediction
Massive separation bubble crossing RHI planes
s270
s310
- 2 RHI scans (azimuth 275 and 290) are analysed
for 2 distinct wind directions (270 and 310)
Not really explained by slopes exceeding
critical angles
Still not explained, even when making critical
angles a function of forestry height. ?
Separation off forestry edge?
13CFD vs LIDAR sector 270 - LOS Velocity
RHI 1
RHI 2
GALION
CFD
14CFD vs LIDAR sector 310 - LOS Velocity
RHI 1
RHI 2
GALION
CFD
Vref 10 m/s _at_ 30m
15CFD vs LIDAR sector 310 - LOS Velocity
RHI 1
RHI 2
GALION
CFD
Vref 18 m/s _at_ 30m
16Conclusions
- Simulations with stability showed significant
improvement in average wind speed cross
predictions, particularly so at difficult mast
location - Decent prediction of TI at 70m from purely
neutral simulation, but TI ratio by direction
between masts better reproduced when free stream
stability is included. - Massively separated flow region seen in CFD for
specific wind directions. - Not necessarily explained by slopes alone.
- Even taking effect of forestry into account on
reduction of critical slope for separation does
not seem to explain why the flow separates so
much more for sector 310 than 270. - ? likely that separation is induced by well
defined forest edge - Massive flow separation for sector 300-310
confirmed by Galion LIDAR data