Vortex Generator Performance

Measurement Challenges and Solutions

Nick Johansen Commercial Operations System Engineer

Sandia Blade Reliability Workshop

August 28, 2014

2

Presentation Outline

1 Experimental Set-up

2 Performance Assessment Toolset

• Site Wind Climatology and Test/Control Period Definitions

3 Performance Assessment Method 1: Power Curve

4 Performance Assessment Method 2: Active Power Relationships

5 Conclusions/Next Steps

3

Experimental Test Set-up

• Mean Site Altitude: 1446m (~4750’) -> 80m Annual Avg. Air Density 1.04 kg/m3

• Annual Average Wind Speed: 8.7 m/s

• Turbulence Intensity less than IEC specification for all operational wind speeds

4

Performance Assessment Toolset

5

Site Wind Climatology/Test Period Definitions

6

0 0.2 0.4 0.6 0.8 1 1.20

0.2

0.4

0.6

0.8

1

Wind Speed (normalized)

Pow

er

(norm

aliz

ed)

Test Period (subset) Power Curves

vg

no vg

• Ambient turbulence intensity inflow conditions from

test and control periods similar for wind speeds

with largest power curve difference

• Change in energy to be calculated per wind speed

bin and a function of control turbine performance

• Test period subsets used to illustrate sensitivity of

energy change to inflow conditions

Performance Assessment: Power Curve

0 0.2 0.4 0.6 0.8 1 1.20

0.2

0.4

0.6

0.8

1

Wind Speed (normalized)

Pow

er

(norm

aliz

ed)

Control Period Power Curves

vg

no vg

0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 10

0.05

0.1

0.15

0.2

0.25

0.3

0.35

0.4

0.45

0.5

Hub Height Wind Speed (normalizwed)

Turb

ule

nce I

nte

nsity

Ambient Turbulence Intensity Comparison

Control

Test

TiA

=17.9504

TiB=15.7066

TiC=13.4628

Control Test

With VG

w/o VG

7

• Active power from VG turbine is plotted as

function of active power from control

turbine (control and test periods)

• Variations in relationship attributed to vg

install

• Requires proper definition of

control and test period

• No reference wind speed is used (nacelle

or free-stream)

• Breaking test periods into subsets -> yields

more independent estimates using all 9

pairs

• Distribution of energy capture differences

established

• Time of year/inflow conditions

sensitivity identified

• Distribution significantly cleaned up with

use of more representative control periods

Performance Assessment: Active Power

Relationships

What conditions caused these estimates?

8

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 10

0.2

0.4

0.6

0.8

1

Power Output (w/o VG) (normalized)

Pow

er

Outp

ut

(w V

G)

(norm

aliz

ed)

Active Power v Active Power Relationship

Control AVG

Control AVG-STD

Control AVG+STD

Test AVG

Test AVG-STD

Test AVG+STD

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1

101

102

Turbine with Vortex Generator Power Standard Deviation Sensitivity to Generation Level

Power Output (w/o VG) (normalized)

Pow

er

ST

D a

s P

erc

enta

ge o

f P

ow

er

Outp

ut

(%)

Control Period

Test Period

• Active power relationship produces

clear signal w/o use of wind speed

• Reduction in power scatter on vortex

generator turbine

• Cleaner loads?

• Spike in power fit standard deviation

associated with region of largest

difference between VG and control

turbine

• VG turbine outperforms control

turbine

• Results associated with specific

inflow conditions • Repeat for other test period subsets

• Matrix of results to inflow conditions

is produced

Active Power Relationships (cont’d)

Variable Speed Fixed Speed

Pitch>0

9

• Inflow conditions in control and test periods to be as close

as possible • Balance between proximity in time or proximity in inflow conditions

• Active power relationship methodology yields multiple

estimates of energy capture improvements • Seasonal/inflow sensitivity identified

• Nacelle wind speed independent

• Power curve approach useful although yields fewer

estimates of energy capture change • Upwind wind resource required can limit useable sectors

• Performance of vortex generators understood at test site(s) • Performance assessment method designed such that results can be

applied to other sites

Conclusions

10

• Instead of just matching seasons for control and test periods,

match exact inflow conditions • Wind direction, wind speed and directional shear, turbulence

intensity, atmospheric stability, inflow angle

• VG energy capture improvement of 1-2% estimate is often

determined through careful filtering of inflow conditions (non-wake

scenarios) • For sites that have significant energy capture with close to mid-

distance waked inflow, how does the 1-2% change

• Do VGs impact performance at low wind speeds and high

turbulence where high turbulence is known to improve energy

capture already?

Next Steps