Calculation of atmospheric stability used for wake …€¦ · Calculation of atmospheric stability...

DTU Wind Energy Department of Wind Energy

Calculation of atmospheric stability used for wake analysis

Kurt S. Hansen & Søren Ott

DTU Wind Energy

kuhan@dtu.dk

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2 DTU Wind Energy, Technical University of Denmark

Outline

1. Background & motivation;

2. Models and required signals;

3. Introduction to AMOK;

4. Examples based on Horns Rev and Lillgrund WF;

5. Horns Rev park efficiency;

6. Conclusion and future work;

7. Acknowledgement.

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Short background (ksh)

• Wind & load measurements (winddata.com);

• Far wake analysis; 3 – 70D (WF SCADA data & Load measurements);

• Near wake analysis; 1 – 3D; (Horiz. Lidar measurements)

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Motivation

Detailed wind farm analysis need a quantification of

Wind direction/spacing;

Wind speed;

Turbulence;

Stratification;

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Models used to determine the atmosperic stratification

Richardson number Ri(h,Δu, Δθ,Ta) Reference: IEA Rec. #3, 1990;

Gradient method (Δu), not completed;

Sonic 3-D+Ta;

Stability based on Froude number, Reference: Javier Sanz Rodrigo/CENER;

Bulk-Ri(h,Δu, Δθ, Ta) method & zref/L = f(Rib); Reference: B.Lange, PhD Thesis;

Monin-Obukov theory (AMOK) zref/L≈g(Rib); Reference: Søren Ott et.al.;

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Method: Bulk-Ri (B.Lange et.al.)

2)(

01.081.9

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T

hRih

a

b

tionstratificastableforRi

RiLz

tionstratificaunstableforRiLz

b

bref

bref

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Ref. The impact of turbulence intensity and atmospheric stability on power deficits due to wind turbine wakes at Horns Rev wind farm; Kurt S. Hansen et.al. WIND ENERGY 2011, we510

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Method: Bulk-Ri (B.Lange et.al.)

Conclusion: Result was not robust, (Søren was not satified)!

Input: HR-M2 1999-2002

Ta: Absolute air temperature, h=55 m

Tw: Sea surface temperature, h=-4 m

Uh: Wind speed, h=62,

Output:

Monin-Obukhov length scale(zref/L)

Input: HR-M7 2005-2007

Ta: Absolute air temperature, h=55 m

Tw: Sea surface temperature, h=-4 m

Uh: Wind speed, h=20,

Output:

Monin-Obukhov length scale(zref/L)

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3-D sonic anemometer

• Input signals from one 3-D sonic anemometer;

• Stab=zref/L

• Comment: Applicable for onshore sites – but not verified for offshore locations

''4.081.9/)273(L3* twuTa

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Determination of offshore stratification - AMOK

• Theory: Monin – Obukhov

Characteristic temperature:

Friction velocity:

MO-length L:

AMOK is a tool for analysing of offshore met data

Input:

<U> <Dir> < Tair > < Twater > <time>

Output: 1/L, θ*, u* (S.Ott)

)/(/1 2

** uTgL a

** /´´ uw ½

* ´´ wuu

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Constants

AMOK version 1.0.3 Output

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Classification of atmosperic stability (offshore)

Class Obukhov length [m] Atmospheric stability class

cL=-3 -100 <=L <= -50 Very unstable (vu)

cL=-2 -200 <=L <= -100 Unstable (u)

cL=-1 -500 <= L <= -200 Near unstable (nu)

cL=0 |L|>500 Neutral (n)

cL=1 200 <= L <= 500 Near stable (ns)

cL=2 50 <= L <= 200 Stable (s)

cL=3 10<= L <= 50 Very stable (vs)

Method: AMOK

Input: - Absolute air temperature, h=13m

- Water temperature, h=-4m - Wind speed, h=15m

Output:

- Monin-Obukhov length (1/L)

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Classification of stratification

Horns Rev- sectorwise atmospherie stability; 7 - 9 m/s (AMOK)

0%

20%

40%

60%

80%

100%

0 30 60 90 120 150 180 210 240 270 300 330

Flow sector - deg.

PD

F -

%

vs

s

ns

n

nu

u

vu

HR-M2:1999-2002

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Stratification at Horns Rev 1999-2002

Wind speed (m/s), h= 62 m

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Preliminary results

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Distribution of turbulence intensity

Fitted with a LogNormal Distribution

NOT DE-TRENDED

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Example: Lillgrund offshore wind farm

N

Mast

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Classification of stratification at Lillgrund WF

Input signals: 0-360 deg

• Inflow wind speed, h=70m (derived from wt power/pitch values);

• Inflow wind direction, h=70m (derived from wind turbine yaw position);

• Air temperature, h=8 m;

• Water temperature measured at Drogden fyr (hourly), Δd>10km;

• AMOK version 1.03;

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Classification of stratification at Lillgrund WF

Stratification@Lillgrund: U = 8 - 10 m/s (2000 hours)

0

5

10

15

20

25

30

-3 -2 -1 0 1 2 3

Stability classification

pd

f [%

]

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Stable

Unstable

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Input: HR-M6 ta: Air temperatur at height, h= 16m; U: Wind speed at height, h= 20m; ts: Sea surface temperature, h=-4m;

Output: Monin-Obukhov length scale

length(1/L); U*, θ*;

Mean turbulence intensity

HR-M7: 2005-2009

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Quantification of power deficit – caused by stratification

• Extract power deficit for 0 – 360°

All observations - reference

Stable stratification (vs,s)

Neutral stratification (ns,n,nu)

Unstable stratification (u,vu)

• Demostration wind farm: Horns Rev (80x2 MW)

• Results for wind speed 8±1 m/s

• Reference wind speed ≈ ”free” wind turbines ~ 100%

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Example: Horns Rev offshore wind farm: 80 x 2 MW, D=80m

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Example of power deficit along wind turbine rows with 7D internal spacing.

Narrow

inflow

sector = 5 deg Narrow sector, Δ=5o

Large sector, Δ =30o

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Efficiency polar

PRELIMINARY

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Park efficiency (Δ AEP):

μi = AEP160MW/80*AEP2MW ; for vi=4±0.5, 5±0.5,..24±0.5 m/s

7-8%

Δ A

nnual Energ

y P

roduction

PRELIMINARY

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Conclusion

• Robust classification of stratification for offshore locations has been established and demonstrated;

There is a lack of high quality measurement:

1) Meteorological flow reference measurements (speed & direction);

2) Wind Farm SCADA data;

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Future work

• Validate and implement the AMOK classification for other offshore sites;

• Determine the dependence of structural loads due to atmospheric stability;

• Results from Horns Rev and other sites will be used in future IEA Wakebench model validations.

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Acknowledgement

The research has been performed in part by EUDP 64010-0462 which is funded by the Danish Energy Agency.

We acknowledge Vattenfall AB and DONG Energy A/S for using the SCADA data from the Horns Rev offshore wind farm.

We acknowledge Vattenfall AB for using the SCADA data from the Lillgrund offshore wind farm.