Saarblitz, Wind farm in HDR, flickr.com, creative commons by-nc-sa 2.0

DWM

The Dynamic Wake Meandering method uses the wind speed deficit of the upstream turbine together with a meandering process in order to simulate the incoming flow field of the downstream turbine and thereby enabling detailed analysis of both production and loading through aeroelastic computations. The meandering process causes an intermittent appearance of the flow field with periods of full, half or no wake situation—varying from time to time driven by the low frequency large-scale natural turbulence.

Latest version

DWM-HAWC2

Submitted by Torben Juul Larsen on May 4, 2015 - 5:42pm
Main hypothesis

The Dynamic Wake Meandering method uses the wind speed deficit of the upstream turbine together with a meandering process in order to simulate the incoming flow field of the downstream turbine and thereby enabling detailed analysis of both production and loading through aeroelastic computations. The meandering process causes an intermittent appearance of the flow field with periods of full, half or no wake situation—varying from time to time driven by the low frequency large-scale natural turbulence.

Software
Solver
HAWC2
License
Regime
Turbulence
Turbulence closure
Turbulence model

The turbulence model for the atmospheric turbulence is based on the Mann model (Mann, 1998).

Atmospheric boundary layer
Coriolis
No
Atmospheric Stability
Atmospheric Stability
Yes
Stability model
Stability included by adjusting turbulence parameters like length scale, degree of isotropy and turbulence intensity
Canopy
Forest canopy
No
Wind farm
Wind turbine
Yes
Rotor model
Wake model
Wind farm range
Additional information

The rotor load simulation for the upwind turbines is based on a blade element momentum theory, as used in the core of the aeroelastic model HAWC2. This calculates the local reduced wind speed, at the assumption of uniform average free wind speed at the location of these rotors. The reduced wind speeds (the deficit) is recalculated for the downstream location in focus using first a model for the near wake pressure recovery and a thin shear layer approximation of the Navier–Stokes equations in their rotational symmetric form for the mixing further downstream. Please see (Madsen et al., 2010) for more details.

Multiple wake conditions are handled in a simple way, where only wake from the turbine causing the largest individual reduction in wind speed is used. Please see (Torben et al., 2012) for further details.

References

Larsen GC, Madsen HA, Thomsen K, Larsen TJ. Wake meandering—a pragmatic approach. Wind Energy 2008; 11:377–395.

Larsen, Torben J. ; Larsen, Gunner Chr. ; Aagaard Madsen, Helge ; Hansen, Kurt Schaldemose. Wind farm production estimates. Part of: Proceedings of EWEA 2012 - European Wind Energy Conference & Exhibition, 2012, EWEA - The European Wind Energy Association.

Madsen HA, Larsen GC, Larsen TJ, Troldborg N. Calibration and validation of the dynamic wake meandering model for implementation in an aeroelastic code. Journal of Solar Energy Engineering 2010; 132(4): 041014-1–041014-14. DOI: 10.1115/1.4002555.

Mann J., 1998, Wind Field Simulation. Probabilistic Engineering Mechanics 13(4): 269–283. Elsevier Science.

Torben J. Larsen, Helge Aa. Madsen, Gunner C. Larsen and Kurt S. Hansen. Validation of the dynamic wake meander model for loads and power production in the Egmond aan Zee wind farm. Wind Energ. (2012). DOI: 10.1002/we.1563.

Content Visibility

Public

Versions