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100
90
80
WF-15 min
WF-30 min
WF-60 min
WF-2 h
WF-4 h
WF-8 h
WF-12 h
70
60
50
40
30
20
10
0
0
10
20
30
40
50
60
70
80
90
100
Power fluctuation (
±
% available capacity)
Figure 5.15
Single wind farm power fluctuations - cumulative distribution
The same information can be expressed much more informatively as a cumu-
lative distribution graph (Figure 5.15). For a lead time of 15 minutes, the magnitude
of the wind power fluctuations is likely (
>
95 per cent probability) to be less than
20 per cent of wind farm capacity, and unlikely (
>
99 per cent probability) to
exceed 30 per cent. A similar pattern is seen for 30 minutes, 1 hour and 2 hour lead
times, except that the most likely maximum variation increases from 26 to
34 per cent and 44 per cent. Over the period of 4 hours, the probability of a
20 per cent maximum variation in output still remains high at 67 per cent, but the
likelihood of greater variations are noticeably increased. Finally, over a 12 hour
period, variations in output of less than 10 per cent occur only one third of the time,
while the probability of a 50 per cent or greater variation in wind power output
almost exceeds 20 per cent.
5.3.2.3 Regional wind farm variability
If the outputs of several wind farms, distributed over a wide area, are now com-
bined together, the observed variability of normalised production should decrease.
Consider the case of a weather front travelling across uniform terrain at a speed of,
say, 8 m/s (29 km/h). If a disturbance were to occur in the weather front, then the
same disturbance would be felt 1 hour later 29 km away. So, by dispersing wind
farms over a large area a degree of smoothing is likely to occur. Of course, the time
delay in the disturbance will be reduced at higher wind speeds, and increased
at lower wind speeds, but the benefit still remains. Similarly, within a wind farm,
the physical separation between each turbine implies that they each experience a
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