DATA VALIDATION - Wind Resource Assessment: A Practical Guide to Developing a Wind Project - page 119

(except when one anemometer is in the tower shadow); wind shears between heights
should fall within reasonable bounds (which may vary diurnally and seasonally).
Table 9-2 gives examples of several relational test criteria for 10-min data. These
tests should ensure that physically improbable situations (such as a significantly higher
speed at 25 m compared to 40 m) are scrutinized. Comparisons between paired sensors
at the same height are especially valuable.
Scatter plots of the speed ratio between a pair of sensors at the same height as
a function of speed can be helpful for detecting problems. Figure 9-2 illustrates two
cases, the first exhibiting a normal degree of scatter and the second an abnormal degree
caused most likely by degradation or damage in one or both of the anemometers.

Table 9-2. Examples of relational test criteria
Parameter a Validation criteria

Wind Speed
Max. gust vs average Max. gust ≤ 2 . 5 × Avg.

60/40 m Average difference ≤ 3 m/s

60/40 m Daily Max. difference ≤ 5 m/s

60/25 m Average difference ≤ 5 m/s

60/25 m Daily Max. difference ≤ 8 m/s

Wind Speed: Same Height
Average difference ≤ 0 . 5 m/s

Maximum difference ≤ 3 . 0 m/s

Wind Direction
60/25 m Average difference

≤ 20 ◦

Wind Shear Varies with terrain

b

− . <α < .

60/25 m Average 0 05 0 45

a All monitoring levels except where noted.
Source: AWS Truepower.
b Wind shear exponent.

Mast data
Expected

Mast data
Expected

1.4 1.4

1.2 1.2

1.0 1.0

0.8 0.8

0.6 0.6

0 5 10 15 20 0 5 10 15 20

Wind speed (m/s) Wind speed (m/s)

Figure 9-2. Plots of speed ratios as a function of wind speed for pairs of anemometers at the
same height. (a) A generally tight relationship with a normal degree of scatter at low speeds.
(b) This chart suggests that at least one of the two sensors is not performing to specification.
Source : AWS Truepower.