1. ReferencesReferences
ConclusionsConclusions
ObjectivesObjectives
INTEGRATION OF ATMOSPHERIC STABILITY
IN WIND POWER ASSESSMENT THROUGH CFD MODELING
Céline BEZAULT (1) – Guillaume DUPONT (1) – Nicolas GIRARD (2) – Olivier TEXIER (2)
(1) METEODYN – (2) MAIA EOLIS GDF
PO.125PO.125
Recent studies have shown that atmospheric stability plays a relevant role in wind resource assessment results.
According to the measurement data provided to the wind assessment team, several methods like the use of Richardson number can be used to determine the local
atmospheric stability. Moreover, orographical and roughness effects are the two main factors inducing perturbations on the wind flow. Hence, it is important to integrate these
methods into a software solution that predicts the wind flow with accuracy.
This integration has been implemented in the CFD code Meteodyn WT which solves the Reynolds averaged Navier Stokes equations. The results show that the
methodologies enable to correctly fit the measurements profile even in forested areas.
An operating wind farm located in the North East of France is studied and 16 months of data have been collected. The importance of stability effects is evaluated in
comparison to the real production on site and the one computed with CFD taking into account real stability and computations with neutral atmosphere only. Including
atmospheric parameters allows us to reduce the error on mean production from 11% to 1%.
AbstractAbstract
ResultsResults
MethodsMethods
[1] Turner, Journal of Applied Meteorology 1992, Vol 31, p83-91
[2] Businger et al., 1971, flux profile relationships in the atmospheric boundary layer, J.Atmos.Sci 28 , 181 - 189
[3] H. Madsen. A Protocol for Standardizing the Performance Evaluation of Short-Term Wind Power Prediction Models. Technical University of Danemark, ANEMOS project, 2004
[4] Meteodyn WT technical documentation
Wind flow
computed by
CFD
Topography
Roughness
Atmospheric
stability
AEP
Atmospheric stability is important for:
• on site where the average wind speed is low (<6 m/s);
• on offshore site, where the atmospheric stability is
predominant over the orography and the roughness;
• simulation on short period, hour or day, as it is used for short-
term prediction, supervision of operation, and power curves
measurement with site calibration as defined in the standard
IEC 61400-12
Several methods are tested. They depend on the measurements available on site or on a regional met station.
Two methods are used to compute the Richardson number. The
first one takes into account the gradient of wind speed and
temperature. The second one is computed by an iterative
method.
Both Pasquill and Turner methods use regional data and local
value of wind speed. The tables below show the method used
for determining the stability class by Turner method by matching
wind speed and net radiation.
Turner method
In the same time, a domain is created to compute directional characteristics of the flow thanks to the CFD Meteodyn WT. The CFD takes into account local roughness and
topographical data.
Domain radius: 4,000 m
Horizontal resolution at point of interest: 25 m
Vertical resolution: 4 m and geometric progress after 40 m high
Directional results (every 10°): speed-up coefficient, turbulence
intensity, inflow angle, deviation
Neutral class represents between 45% and 63% according to the method. Unstable cases are less
numerous in the method which uses nebulosity data.
Cross analysis has been realized in order to check that for example, a stable case with M1 corresponds
to a stable case with M4.
M1 M2 M3 M4 M5 M6
M1 92.21% 82.08% 84.39% 77.79% 78.68%
M2 76.89% 73.29% 73.29% 73.73%
M3 97.99% 94.40% 79.49%
M4 94.05% 94.82%
M5 99.82%
M6
On the site described in the previous section, the production has
been computed by the CFD Meteodyn WT. Considering that the
atmosphere is always neutral, the production was overestimated
by 11,6%. Less than 1% was found after taking into account the
distribution of stability in the AEP computations.
The different methods have been tested according to the measurements available on site or on a regional met station. The methods are consistent and have been validated
on a site located in a complex and forested terrain. The improvement in the AEP computation has been proven. More test cases must be executed before integrating this
methodology into the CFD Meteodyn WT. Some limitations can be the precision of the temperature sensor (0.1°C) and some uncertainties such as roughness calibration.
Methods used according to met mast data / regional station