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Tom Hodkinson, Simon Watson & Paul Rowley

This study examines the underperformance of urban wind turbines focusing on yaw misalignment effects, turbulence intensity, and rotor inertia. Research conducted with novel sensors and published power curve data reveals significant energy loss due to yaw errors.

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Tom Hodkinson, Simon Watson & Paul Rowley

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  1. 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 Rowley Centre for Renewable Energy Systems Technology, School of Electronic, Electrical and Systems Engineering, Loughborough University, UK

  2. Outline • The problem – underperformance of urban wind turbines • The experiment • The results • The conclusions

  3. Under-performance of urban wind turbines

  4. 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

  5. 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

  6. Turbine and Sensors • Yaw sensor made from an adapted wind vane

  7. Site Meteorological Characteristics Wind Speed Distribution Wind Roses 1st data period – 720 hours 2nd data period – 672 hours Turbulence Intensity

  8. Turbine Performance Published power curve Raw data points Bin averaged Large discrepancy

  9. Yaw Misalignment

  10. Yaw Misalignment and Rate of Change of Wind Direction Accurate tracking <10 degrees/second Steep rise in error 10-20 degrees/second

  11. Yaw Error and Power Output 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%.

  12. 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

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