EWEA February 4-7, 2013Vienna, Austria

Wind Farms in Complex Terrain: Numerical Simulation of Wind and Wakes for Optimized Micrositing

S. Jafari, N. Chokani, R.S. AbhariETH Zürich, Switzerland

February 6, 2013 Samira Jafari 2

Overview Motivation

Objectives

Modeling Approach: Immersed Wind Turbine Model

Validation and Results

Single Wake

Multiple Wake

Wind farm in complex terrain

Summary and Conclusion

February 6, 2013 Samira Jafari 3

Motivation Wind turbines operating in wakes of upwind wind turbines may have

30-40 % power losses compared to upstream turbine

up to 80% larger fatigue loads than upstream turbine

Most models fail in predictions when more complex inflow or ground features are

present

Interaction of topography with wake and wind flow not addressed satisfactorily to

date

Microscale wind and wake flow must be simultaneously simulated to be able to:

Account for change in inflow wind due to terrain effects

Assess effect of elevated turbulence on wake’s evolution

Investigate interaction of wake with adverse/favorable pressure gradients caused by

topography

February 6, 2013 Samira Jafari 4

Objectives Develop computationally efficient wake model to be embedded in RANS solver

used for microscale wind simulations with comparable grid requirements

Perform simultaneous simulations of microscale wind and wind turbine wake

Validate and evaluate predictions of flow field and power performance in wind

farms

February 6, 2013 Samira Jafari 5

Numerical Approach Turbines modeled using immersed wind turbine model (IWTM), embedded in

LEC’s RANS solver, MULTI3

Turbine represented as streamtube defined based on turbine operating point

Near wake modeled, velocity and turbulent field mapped at the end of inviscid

expansion of wake, but far wake resolved on computational grid

Boundary conditions imposed on Cartesian grid using immersed boundary

method

February 6, 2013 Samira Jafari 6

Validation: Microscale Wind Prediction of wind speed compared with field measurements over Askervein

(moderate terrain, Jafari et al., 2011) and Bolund Hill (complex terrain, Jafari et al., 2012)

Good agreement observed for both cases, up- and downstream of hillAskervein Hill Bolund Hill, 270o

February 6, 2013 Samira Jafari 7

Mean Flow of Single Wake Predicted evolution of wake in good agreement with wind tunnel experiments,

(Hassan,1992)

Maximum 12% difference between predicted and measured wind speed

February 6, 2013 Samira Jafari 8

Turbulence Intensity in Single Wake At x=2.5D, two peaks observed in turbulence intensity profile as expected

Evolution of turbulence intensity captured well both qualitatively and qualitatively

February 6, 2013 Samira Jafari 9

Single Wake: Full-scale Measurement Predictions compared

with full-scale

measurements at

Sexbierum wind farm

5.4 MW farm

consisting of 18

turbines, D=30 m

Maximum deficit

underestimated by

20%

Wake width predicted

well

February 6, 2013 Samira Jafari 10

Validation: Multiple Wakes Interactions of multiple wakes examined for offshore wind farms

Horns Rev (offshore, Denmark), 80 Vestas V2.8-80

Lillgrund (offshore, Sweden), 48 Siemens SWT-2.3-93

28 2730

Power loss in array and sensitivity to wind direction captured for all cases

February 6, 2013 Samira Jafari 11

Wind Farm in Complex Terrain 23.7 MW Mont Crosin wind farm located in Jura region, Switzerland (complex

terrain) consisting of 16 turbines with hub heights of 45 and 95 m

SCADA data collected and analyzed over one and a half years period

270o

February 6, 2013 Samira Jafari 12

Simulation Set-Up Upstream conditions of wind speed and turbulence and specified based on:

Long-term mesoscale [Weather Research Forecast Model (WRF)] simulations

performed over Switzerland, Jafari et al., 2012

Measurements using LEC’s nacelle mounted probe, Mansour et al., 2013

Computational grid for wind direction 170o Dominant wind direction from south-west quadrant

February 6, 2013 Samira Jafari 13

Mont Crosin Wind Farm: Results Impact of terrain on local wind evident

Performance of turbine 14 decreases

relative to turbine 13 up to 65%

260o

260o

230o

90 m AGL

45 m AGL

February 6, 2013 Samira Jafari 14

Summary & Future Work Simultaneous simulation of microscale wind and wakes accomplished with

computationally efficient wind turbine model

Model evaluated with broad range of test cases including wind tunnel/field

experiments, onshore/offshore, and flat/complex terrain

IWTM brings grid requirements for wake simulations closer to microscale wind

and facilitates use of Computational Fluid Dynamics for micrositing in complex

terrain

February 6, 2013 Samira Jafari 15

Thank you.