Equivalent wind speed for AEPRozenn Wagner

VindKraftNet03-11-2011Risø

Risø DTU, Danmarks Tekniske Universitet

Experimental setup & Data processing

Filters:• wind direction;• no rain;• lidar signal availability 100% atall heights;• turbine status=1.

N

Risø DTU, Danmarks Tekniske Universitet

Profiles classification

( )fit

mfit hub

hub

zu z uz

α

=

( )2( ) mfit i i

i

RSS u z u= −∑RSS<0.1

RSS>0.1

Risø DTU, Danmarks Tekniske Universitet

Standard power curve

� 2 groups of profiles result in 2 different power curves

Risø DTU, Danmarks Tekniske Universitet

Equivalent wind speed

A1

A2

A3

A4

A5

Concept:

One wind speed representative ofthe whole wind speed profile in frontof the wind turbine rotor in term ofpower production

U1

U2

U5

U4

U3 Ueq

1/3 1/33 3

1

1 ( ) ( )R N

iKE i

iR

AU u z c z dz uA A=−

= ≈ ∑∫

Definition:

Risø DTU, Danmarks Tekniske Universitet

Power curve with equivalent wind speed

� Similar power curves are obtained for both groups of profiles

Risø DTU, Danmarks Tekniske Universitet

Comparison of the power curves

Difference due to the sheardistribution during the powercurve measurement.

How can theequivalent wind speedpower curve be usedfor AEP estimation?

Risø DTU, Danmarks Tekniske Universitet

Annual Energy Production

XAEP

Power curve atwind farm site

Wind speed distributionat wind farm site

=

Risø DTU, Danmarks Tekniske Universitet

AEP estimation

XPredictedAEP

Reference power curve:measured at a reference site

=

Wind speed distributionat wind farm site

Uhub power curve Uhub distribution

Ueq power curve Ueq distribution

Uhub power curve Uhub distribution

Ueq power curve Ueq distribution

Risø DTU, Danmarks Tekniske Universitet

Illustration of the 2 cases with Høvsøre data

DataGroup 1

Reference site

Reference power curve

DataGroup 2

Estimated site

Measured windspeed

Total power estimation

case1: with uhub

case 2: with Ueq

Risø DTU, Danmarks Tekniske Universitet

Illustration of the 2 cases with Høvsøre data

prediction: + 1.76%

Case 1

Risø DTU, Danmarks Tekniske Universitet

Illustration of the 2 cases with Høvsøre data

prediction: + 1.76% prediction: 0.005%

�Improved AEP estimation by using the equivalent wind speed both inthe power curve and the wind speed distribution.

Case 1 Case 2

Risø DTU, Danmarks Tekniske Universitet

More realistic applicationPower curve and wind distribution from 2 separate sites

Høvsøre

Østerild

Risø DTU’s Test Site for Large TurbinesHøvøsre

Risø DTU, Danmarks Tekniske Universitet

Power curve measured atHøvsøre in Feb-March2009

Wind speed distributionmeasured at Østerild May2010- May 2011

�

��

�

�

�

�����

��

��

��

��

��

����

�

��

�

�

�

����

��

���

��

��

��

����

4 6 8 10 12 140

100

200

300

400

�m�s�nbhours

All

4 possible combinations, but no turbine yet.

More realistic applicationPower curve and wind distribution from 2 separate sites

Risø DTU, Danmarks Tekniske Universitet

Combination 1:

•Equivalent power curve

•Equivalent wind speeddistribution

� Account for the shear during the powercurve measurement; expected to be thesame power curve at any site

� Account for the shear at Østerild

Reference AEP

Risø DTU, Danmarks Tekniske Universitet

Combination 2:

•Hub height power curve

•Hub height wind speeddistribution

-2.3%

� Underestimates the power producedbecause of the shear during the powercurve measurement.

� Slightly underestimates the energyavailable because does not account forthe shear at Østerild (assumes flat windspeed profiles)

Risø DTU, Danmarks Tekniske Universitet

Combination 3:

•Equivalent power curve

•Hub height wind speeddistribution

-0.5%

� Account for the shear during the powercurve measurement; expected to be thesame power curve at any site

� Slightly underestimates the energyavailable because does not account forthe shear at Østerild (assumes flat windspeed profiles)

Risø DTU, Danmarks Tekniske Universitet

Summary

U_hub power curve Ueq power curve

U_hub distribution (-2.3%) (-0.5%)

U_eq distribution (ref)

The error depends both on:• the Ueq/Uhub distribution during the power curve measurement (-1.8%)• and the Ueq/Uhub distribution at the assessed site (-0.5%)

Risø DTU, Danmarks Tekniske Universitet

More examples

Ueq/Uhub> 1Ueq/Uhub< 1

Risø DTU, Danmarks Tekniske Universitet

Case1: Ueq/Uhub> 1

U_hub power curve Ueq power curve

U_hub distribution (-3.8%) (-2.1%)

U_eq distribution (ref)

Profiles with larger kinetic energy than flat profiles

Part of the the error due to Ueq/Uhub distribution at the assessed site largerthan before (-2.1%);� Overall error larger than previous case.

Risø DTU, Danmarks Tekniske Universitet

Case2: Ueq/Uhub< 1

U_hub power curve Ueq power curve

U_hub distribution (0.00%) (+1.8%)

U_eq distribution (ref)

Profiles with smaller kinetic energy than flat profiles

Specific case:The Ueq/Uhub distribution are verysimilar for both datasets.

Risø DTU, Danmarks Tekniske Universitet

Conclusions 1

The shear influences the AEP estimation in 2 ways:

1)Error in power curve due to the shear during the power curvemeasurement2)Error in available energy at the assessed site.

�Missing uncertainty terms in the standard AEP estimation

�Equivalent wind speed results in a repeatable power curve.

�Improved AEP estimation with equivalent wind speed

�It requires to measure the wind speed profiles for site assessment

Risø DTU, Danmarks Tekniske Universitet

Conclusions 2

What to do if the equivalent wind speed distribution at the assessed site isnot available?

� If the Ueq/Uhub distributions at the two sites are similar: use the standardAEP calculation (wind speed at hub height).

� If the Ueq/Uhub distributions are different: combine the hub height speeddistribution with the equivalent power curve.

But to know the Ueq/Uhub distribution…… you need to measure the shear!

Acknowledgement: EU SafeWind

Risø DTU, Danmarks Tekniske Universitet

Wind lidar calibration

•Comparison to cupanemometers at 5 heights

•Horizontal wind speed,sensing height error,uncertainty, direction

•Synchronised lidar/mast data

•Accrediation for Windcubescalibration

DANAK

y�0.005 1.005 x

R2�0.998542

y�1.006 xR2�0.998541

4 6 8 10 12 14 16

4

6

8

10

12

14

16

cup �40m �m�s�

lidar

�40m

�m�s�

�� �����������������������

�� �����������������������

�� �����������������������

4 6 8 10 12 14 160.6

0.4

0.2

0.0

0.2

0.4

0.6

ref wind speed �40m �m�s�

lidarerror�40m

�m�s�

Risø DTU, Danmarks Tekniske Universitet

Wind lidar measurement

•Rent out a Windcube

•Set up, data transfert

•Data analysis

Risø DTU, Danmarks Tekniske Universitet

Wind Lidar – A practical course7-10 May 2012

•Lectures about the workingprinciples and limitations of lidarsystems.

•Interpreting data

•Hands-on experience with a lidaron-site

More information and registrationhttp://www.risoe.dtu.dk/da/conferences/vea_lidar_course_2012.aspx?sc_lang=en