(… or, how did we end up here anyway)

There was an old lady who swallowed a fly …

Limited measurement opportunities

There was an old lady who swallowed a fly …

Approximations to compensate for lack of knowledge, e.g. • Wind shear exponent, • Turbulence intensity

There was an old lady who swallowed a spider …

𝑽 (𝒛 )=𝑽 𝒉𝒖𝒃( 𝒛𝒛𝒉𝒖𝒃

)∝

0 0.2 0.4 0.6 0.8 1 1.2 1.40

0.5

1

1.5

2

Hei

ght /

hub

hei

ght

Wind speed / hub height wind speed

Solutions that are over-constrained by the original problem can lead to

bigger problems

There was an old lady who swallowed a horse …

… she’s dead, of course.

Eolics: equally sophisticated• Measurements • Models of atmospheric conditions and wind turbine response

Scientific rigour and predictive power is possible

There was an old lady who didn’t swallow a fly …

(… or, what would we do if we started from scratch)

• My knowledge is incomplete

• The incompleteness of my knowledge extends to my knowledge of its incompleteness

• I don’t know what I don’t know

• Do you know what I don’t know I don’t know?

• We cannot predict what we can learn from each other

• Measure, discuss, disagree … learn

Epistemology and the eolicist

Compression zone

EnergyEnergy

Energy

Compression zone

© Gerrit Wolken-Möhlmann, Fraunhofer IWES

Galion G4000 Offshore on transition piece

2 x Galion G4000 Offshore on nacelle, one facing forward to survey inflow, one facing back for wakes

© Gerrit Wolken-Möhlmann, Fraunhofer IWES

Unit G24Compression zone

Compression zone

Compression zone at 5m/s

Compression zone

90%

91%

92%

93%

94%

95%

96%

97%

98%

99%

100%

101%

102%

103%

104%

105%

5 m/s bin6 m/s bin7 m/s bin8 m/s bin9 m/s bin10 m/s bin11 m/s bin12 m/s bin

Upwind distance from rotor (m)

Nor

mal

ised

win

d Sp

eed

(% o

f win

d sp

eed

at 2

.5D

upw

ind)

2.5D = 100%

Free streamNacelle lidar

Convergent scan geometries

Mast

Convergent scan geometries

MastTB1

TB2

Convergent scan geometries

Convergent scan geometries

0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.40

0.05

0.1

0.15

0.2

0.25

0.3

0.35

0.4f(x) = NaN x + NaNR² = 0

Mast Turbulence Intensity

Lida

r Tur

bule

nce

Inte

nsity

The problem with turbulence intensity

Linear ramp

Random Gaussian

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 10

0.10.20.30.40.50.60.70.80.9

11.11.21.31.41.51.61.71.81.9

22.12.2

VarianceTransience, m=1 Degree of "scatter"

m2

/s2

Transience versus Variance

n

imiim xx

n 1

22 1

n

ii xx

n 1

22 1