Analysing the Performance of a Building-Mounted Battery Charging Wind Turbine with Particular

Emphasis on the Effect of Yaw Misalignment

Tom Hodkinson, Simon Watson & Paul RowleyCentre for Renewable Energy Systems Technology, School of Electronic,

Electrical and Systems Engineering, Loughborough University, UK

Outline

• The problem – underperformance of urban wind turbines

• The experiment• The results• The conclusions

Under-performance of urban wind turbines

Possible Reasons

• High levels of ambient turbulence intensity• Rotor inertia leading to sub-optimal Cp-λ tracking• Non-horizontal flow – steady state or due to

turbulence• Increased yaw misalignment

Loughborough University Urban WT

• Marlec Rutland Wind Charger 913

• Rated at 90W for 10m/s• Battery charging (12V)• Wind speed & direction

measurements• Novel yaw sensor• Investigation of

performance in turbulent environment

Turbine and Sensors

• Yaw sensor made from an adapted wind vane

Site Meteorological Characteristics

010203040506070

0 2 4 6 8 10 12

Turb

ulen

ce In

tens

ity (%

)

Wind Speed (m/s)

Measured original anemometer data in 0.5 m/s wind speed binsMeasured boom anemometer data in 0.5 m/s wind speed bins

1st data period – 720 hours

2nd data period – 672 hours

Wind Roses Wind Speed Distribution

Turbulence Intensity

Turbine Performance

0

10

20

30

40

50

0 1 2 3 4 5 6 7 8 9

Pow

er (W

atts

)

Wind Speed (m/s)Raw measured data Average measured power in 0.5 m/s wind speed bins Power output given by [19]

Raw data points

Bin averaged

Published power curve

Large discrepancy

Yaw Misalignment

-180-150-120 -90 -60 -30 0 30 60 90 120 150 1800

1

2

3

4

Yaw Error (Degrees)

Prob

abili

ty D

ensit

y (%

)

0 to 1 m/s 1 to 2 m/s 2 to 3 m/s 3 to 4 m/s5 to 6 m/s 6 to 7 m/s > 7 m/s

Yaw Misalignment and Rate of Change of Wind Direction

Accurate tracking <10 degrees/second

Steep rise in error 10-20

degrees/second

Yaw Error and Power Output

𝑃 𝐿=1− (cos𝜃𝑦𝑎𝑤 )3

Fractional Power Loss (PL) should be approximately related to the cube of the yaw misalignment:

From the measured yaw misalignment this gives a predicted energy loss of 19% compared to the actual loss of 41%.

Conclusions

• Capacity factor was found to be 3.6%• Yaw error:

• <2m/s, large errors• 2m/s-7m/s, the SD of yaw error decreases 32˚ 24˚• >7m/s, the yaw error starts to increase again

• Yaw response:• wind direction changes <10˚/sec, av. yaw error is zero• yaw error increases rapidly for changes >10˚/sec

• Overall energy loss (c.f. power curve) found to be 41% with 19% estimated to be due to yaw error