CHARACTERIZING THE OBSERVED WIND RESOURCE - Wind Resource Assessment: A Practical Guide to Developing a Wind Project - page 136

0.16

0.14 Weibull k

1.3
1.7
2
2.4
3

0.12

0.1

0.08

0.06

0.04

0.02

0

0 5 10 15 20 25 30

Speed (m/s)

Figure 10-3. Weibull probability density curves for a range of values of k . All curves have the
same A : 8.0 m/s. Source : AWS Truepower.

It is often handy to refer to the Weibull parameters, particularly k , when character-
izing a site's wind resource. It is important to keep in mind, however, that the Weibull
curve is, at best, an approximation of the true wind speed frequency distribution. While
the real speed distributions at many sites fit a Weibull curve quite well, there are some
sites where the fit is poor, as suggested in Figure 10-4. For this reason, the Weibull
curve should never be used in place of the observed speed frequency distribution when
estimating energy production , except in a preliminary way. Many resource analysts
choose to ignore it altogether.

10.1.8 Wind Rose
In most projects, it is desirable to space turbines much further apart along the principle
wind direction than perpendicular to it to minimize wake interference between the
turbines. For this reason, the directional frequency distribution is a key characteristic
of the wind resources.
A polar plot displaying the frequency of occurrence by direction is called a wind
rose . Wind rose plots often display the percentage of time the wind blows in certain
speed ranges by dividing each segment of the plot into different color bands. Another
type of plot, known as an energy rose , displays the percentage of total energy in the
wind coming from each direction. Sometimes these plots are combined into one. Wind
and energy rose plots are created by sorting the wind data into the desired number of
sectors, typically either 12 or 16, and calculating the relevant statistics for each sector.

100 N i
N
Percentage of total energy : E i

Frequency ( % ) : f i =

100 N i ×

WPD i

=

N × WPD