Wind Energy

118 S. Barth et al.
p(u τ) [a.u.]
10 −4
10 −2
10 −4
10 −6
10 −8
10
−10 0 10
−8
10
uτ /στ −12
10 −10
p(u τ) [a.u.]
−10 0
uτ/στ 10
Fig. 20.3. Atmospheric PDFs: Symbols represent the normalized PDFs of the
atmospheric data sets. Straight lines correspond to a fit of distributions according to
(20.4). All graphs are vertically shifted against each other for clarity of presentation.
Left: sonic anemometer: From top to bottom τ takes the values: 0.5s, 2.5s, 25s,
250 s and 4, 000 s. Right: hotwire anemometer: From top to bottom τ takes the
values: 2 ms, 20 ms, 200 ms and 2, 000 ms
hot-wire anemometer in an atmospheric flow during a period of stationary
mean wind speed. In both cases the scale dependent statistics can be described
with 20.4.
20.3 Conclusions and Outlook
Atmospheric velocity increments and their occurrence statistics are related
to loads on wind turbines. For constructing wind turbines a model that
reproduces the right increment distributions for every location should therefore
be used. Our approach is a good candidate to achieve such a robust model.
References
1. U. Frisch: Turbulence. The Legacy of A.N. Kolmogorov, Cambridge University
Press, Cambridge, 1995
2. B. Castaing, Y. Gagne, E.J. Hopfinger: Physica D 46, 177, 1990
3. T. Burton, D. Sharpe, N. Jenkins and E. Bossanyi: Wind Energy Handbook,
Wiley, New York, 2001