VindKraftNet 03-11-2011 Risø

Experimental setup & Data processing N

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

Risø DTU, Danmarks Tekniske Universitet

Profiles classification

u fit ( z ) = RSS = i

m uhub

(u

Risø DTU, Danmarks Tekniske Universitet

fit

z zhub

m fit ( zi ) ui

RSS0.1

Standard power curve

2 groups of profiles result in 2 different power curves Risø DTU, Danmarks Tekniske Universitet

Equivalent wind speed U1

Concept:

U2

One wind speed representative of the whole wind speed profile in front of the wind turbine rotor in term of power production

U3

Ueq

U4 U5

A1 A2

Definition:

U KE

1 = A

1/3

R 3

u ( z ) c( z )dz R

Risø DTU, Danmarks Tekniske Universitet

Ai u A i =1 N

3 i

1/3

A3 A4 A5

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 shear distribution during the power curve measurement.

How can the equivalent wind speed power curve be used for AEP estimation?

Risø DTU, Danmarks Tekniske Universitet

Annual Energy Production

AEP

X

=

Power curve at wind farm site

Risø DTU, Danmarks Tekniske Universitet

Wind speed distribution at wind farm site

AEP estimation

Predicted = AEP

X

Reference power curve: measured at a reference site

Wind speed distribution at wind farm site

Uhub power curve

Uhub distribution

Ueq power curve

Ueq distribution

Risø DTU, Danmarks Tekniske Universitet

Illustration of the 2 cases with Høvsøre data Data Group 1 Reference site

Reference power curve

Data Group 2 Estimated site

Measured wind speed

Total power estimation case1: with uhub case 2: with Ueq Risø DTU, Danmarks Tekniske Universitet

Illustration of the 2 cases with Høvsøre data Case 1

prediction: + 1.76%

Risø DTU, Danmarks Tekniske Universitet

Illustration of the 2 cases with Høvsøre data Case 1

Case 2

prediction: + 1.76%

prediction: 0.005%

Improved AEP estimation by using the equivalent wind speed both in the power curve and the wind speed distribution. Risø DTU, Danmarks Tekniske Universitet

More realistic application

Power curve and wind distribution from 2 separate sites

Østerild

Høvsøre

Risø DTU’s Test Site for Large Turbines Høvøsre Risø DTU, Danmarks Tekniske Universitet

More realistic application

Power curve and wind distribution from 2 separate sites

Power curve measured at Høvsøre in Feb-March 2009

Wind speed distribution measured at Østerild May 2010- May 2011 All

nb hours

400 300 200 100 0

4

6

8

10 m s

4 possible combinations, but no turbine yet. Risø DTU, Danmarks Tekniske Universitet

12

14

Combination 1: • Equivalent power curve

Account for the shear during the power curve measurement; expected to be the same power curve at any site

Reference AEP

• Equivalent wind speed distribution

Risø DTU, Danmarks Tekniske Universitet

Account for the shear at Østerild

Combination 2: • Hub height power curve

Underestimates the power produced because of the shear during the power curve measurement.

-2.3%

• Hub height wind speed distribution

Risø DTU, Danmarks Tekniske Universitet

Slightly underestimates the energy available because does not account for the shear at Østerild (assumes flat wind speed profiles)

Combination 3: • Equivalent power curve

Account for the shear during the power curve measurement; expected to be the same power curve at any site

-0.5%

• Hub height wind speed distribution

Risø DTU, Danmarks Tekniske Universitet

Slightly underestimates the energy available because does not account for the shear at Østerild (assumes flat wind speed profiles)

Summary

U_hub power curve Ueq power curve U_hub distribution

(-2.3%)

U_eq distribution

(-0.5%) (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< 1

Risø DTU, Danmarks Tekniske Universitet

Ueq/Uhub> 1

Case1: Ueq/Uhub> 1 Profiles with larger kinetic energy than flat profiles

U_hub distribution

U_hub power curve

Ueq power curve

(-3.8%)

(-2.1%)

U_eq distribution

(ref)

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

Risø DTU, Danmarks Tekniske Universitet

Case2: Ueq/Uhub< 1 Profiles with smaller kinetic energy than flat profiles

U_hub distribution

U_hub power curve

Ueq power curve

(0.00%)

(+1.8%)

U_eq distribution

(ref)

Specific case: The Ueq/Uhub distribution are very similar 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 curve measurement 2)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 is not available? If the Ueq/Uhub distributions at the two sites are similar: use the standard AEP calculation (wind speed at hub height). If the Ueq/Uhub distributions are different: combine the hub height speed distribution 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 cup anemometers at 5 heights

16

y 0.005 F

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

1.005 x

R2 0.998542

12

y 1.006 x R2 0.998541

• Synchronised lidar/mast data

10 8 0.6

6 4 4

6

8 cup

lidar error 40m m s

lidar

40m m s

14

• Accrediation for Windcubes calibration DANAK

0.4 0.2

0.0 12 0.2 40m m s 0.4

10

0.6

14

4

16

6

8

10

12

ref wind speed 40m m s

Risø DTU, Danmarks Tekniske Universitet

14

16

Wind lidar measurement •Rent out a Windcube •Set up, data transfert •Data analysis

Risø DTU, Danmarks Tekniske Universitet

Wind Lidar – A practical course 7-10 May 2012 •Lectures about the working principles and limitations of lidar systems. •Interpreting data •Hands-on experience with a lidar on-site

More information and registration http://www.risoe.dtu.dk/da/conferences/vea_lidar_course_2012.aspx?sc_lang=en Risø DTU, Danmarks Tekniske Universitet