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154 A. Rauh et al.<br />

2000<br />

1500<br />

1000<br />

500<br />

L<br />

6 8 10 12 14 16<br />

U<br />

1200<br />

1000<br />

800<br />

600<br />

400<br />

L<br />

b)<br />

200<br />

U<br />

0<br />

5 6 7 8 9 10 11 12<br />

Fig. 27.1. (a) Schematic power curve as an attractor. (b) 20-s (U, L) trajectory<br />

in relation to the power curve. Horizontal and vertical units are m s −1 and kW,<br />

respectively<br />

2500<br />

2000<br />

1500<br />

1000<br />

500<br />

L<br />

5 10 15 20 25<br />

Fig. 27.2. Cluster of 10 4 one Hz points (2 MW turbine at Tjareborg)<br />

27.2 Power Curve from Measurement Data<br />

An inspection of the point cluster in Fig. 27.2 suggests to define an empirical<br />

power curve by the location where, in a given speed bin, the maximal density of<br />

points L(ti) is found. This extremal property is expected, if the power curve<br />

is an attractor. In previous work [2], the following expectation values were<br />

considered ∆jk := Uj,Lk with the suffix Uj,Lk denoting<br />

the restriction to the speed and power bin Uj and Lk, respectively. For a<br />

given speed bin Uj, the corresponding point on the power curve was defined<br />

by the power bin L k(j) where ∆ jk(j) changes sign. In practice this may cause a<br />

problem, if for a given speed bin there are several locations with sign change.<br />

The maximum principle, on the other hand, should give a unique result after<br />

properly defining the bin sizes:<br />

U

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