Environmental Engineering Reference
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R xx (z) = [k L (z/ Z )( x 2 /z 2 ) + k T (z/ Z )(1 - x 2 /z 2 )] s 0, x
(8-31a)
(8-31b)
x = y U /W
4 r 2 sin 2 y/2 + x 2
(8-31c)
z =
where
R xx = two-point autocorrelation function for longitudinal winds at A and B
(m 2 /s 2 )
k L ( ), k T ( ) = longitudinal and transverse correlation coefficients evaluated at ( ), refer-
enced to A-B' (Eqs. (8-28) to (8-30))
y = azimuthal coordinate from A to B (rad)
z = distance from A to B' (m)
Inspection of Equations (8-32) reveals that the Eulerian autocorrelation function is obtained
by setting r equal to zero, and the frozen turbulence case is obtained with U equal to zero.
For non-isotropic turbulence, we can define an equivalent isotropic integral scale length as
Z = Z x ( x /z) + Z y (1 - x /z)
(8-31d)
where
Z x , Z y = longitudinal and lateral integral scale lengths, respectively (m)
Powell et al. [1985] found that the best correlation between calculated and measured
Lagrangian spectra from the Clayton, New Mexico, vertical-plane array was obtained when
the integral length scales Z x and Z y were both set equal to about 1.7 times the mid-elevation
of the array. Therefore, a reasonable approach would be to assume isotropic turbulence and
treat Z as an empirical parameter, to be evaluated on the basis of available test data. Powell
and Connell [1986b] provide a computer model for simulating rotational data for both
HAWTs and VAWTs and compare calculated spectra to experimental data.
To illustrate the use of Equations 8-31, we will calculate horizontal autocorrelation
functions for a Mod-OA HAWT, using the Dryden correlation coefficients for simplicity.
The configuration parameters for this sample case are as follows:
R = rotor radius = 19.05 m
W = rotor speed = 4.19 rad/s
h
= hub elevation = 30.5 m
Z = 51 m
U = steady wind speed = 8.21 m/s
s = 0.9 m/s
Figure 8-31 shows typical behavior of the autocorrelation function (normalized by the
square of the turbulence or the variance ) with increasing azimuthal angle, at four radial
locations. The valleys are regions of lower correlation which produce the characteristic
peaks in the Lagrangian power spectrum shown in Figure 8-32. This spectrum is obtained
from the autocorrelation function by a standard fast Fourier transform (FFT) analysis.
VAWT Rotational Sampling
The two-point spatial correlation for a VAWT is developed in the same manner as that
for the HAWT [Powell and Connell 1986a]. Comparisons of simulated Lagrangian spectra
for VAWTs with equivalent spectra for a HAWT [George 1984] indicate much lower turbu-
lent energy for VAWTs in flow fields with strong vertical gradients, as would be expected.
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