Influence of wind characteristics on turbine performance

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• Influence of wind characteristics on turbine
  performance
• Ioannis Antoniou (1), Rozenn Wagner (1), Søren M.
  Pedersen (1), Uwe Paulsen (1), Helge A. Madsen
  (1), Hans E. Jørgensen (1),
• Kenneth Thomsen (2), Peder Enevoldsen (2), Leo
  Thesbjerg (3)
• (1) Wind Energy Department, Risø,DTU
• (2) Siemens Wind Power
• (3) Vestas Wind Systems A/S

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Outline of the presentation

• Background
• Wind profile measurements and classification
• The analysis method
• Aeroelastic simulations
• The wind turbine
• Input modifications
• Sensitivity analysis
• Conclusions

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Background Large Cp power curve variations,
flat and complex terrain

• Large periodic performance changes within a
  short period.
• The changes in the power curve and Cp are not due
  to the incorrect performance of the cup
  anemometers.

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Are performance changes connected to profile
changes and the way performance is measured (hub
height) ?
Stable atmosphere and high wind shear during
night flat, well-mixed during the day
Stable atmosphere with local maximum during the
whole day
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Wind profile measurements and classification at
the Høvsøre test site

• Two met masts used
• Wind speeds measured at
• 10m
• 40m
• 60m
• 80m
• 100m
• 116m
• 165m
• Sector 60 to 120 (larger variations relative
  to the west sector)
• Wind speed 6m/slt Ult8m/s

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Wind profile measurements and classification

• Appr.
• Profiles normalized at 7m/s
• 2500 profiles resulted in 173 profile classes
  (not equally weighted classes)

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Wind profile measurements and classification
Energy Ratio(highest / lowest)gt2
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Wind profile measurements and classification at
the Høvsøre test site

• Examine, with the help of simulations, the
  influence of
• Wind shear
• Turbulence shear
• Direction shear ......on the power curve

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Definition of three weighted (equivalent) wind
speeds
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Aeroelastic simulations

• AE_N_Wind/HAWC2 code
• BEM code implemented in the program
• User defined mean and turbulence shear input
• Validated for W/T Siemens 3.6 MW model.

• Use the normalised profiles as input to identify
  the sensitivity of the wind field parameters on
  the w/t performance (mean shear, turbulence
  shear, wind vector slope and direction changes
  with height).
• Time series simulations, to characterise the
  power performance of the turbine.
• The Mann turbulence model is used to generate the
  turbulence field added to the mean field in order
  to model the random feature of the wind (10
  simulations performed per profile).

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Validation of the code under no-shear and user
extreme shear conditions
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Simulation results using the weighted wind speeds
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Simulation results using the weighted wind speeds
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Goodness-of-fit to the turbines power curve vs.
no of measured profile points
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Measuring the power curve through a blade mounted
Pitot tube
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Measuring the power curve through a blade mounted
Pitot tube
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A probable explanation

• The integration of the wind speed over the pitot
  path, does not weight the wind speeds equally
  over the rotor profile. Some wind speeds are more
  represented relative to other ones.

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Remote sensing using lidars and sodars
AQ500
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Conclusions and future work

• The profiles from a flat test site have been
  measured and classified and large variations have
  been observed in their energy contents
• Aeroelastic calculations confirm the dependence
  between the impinging and the resulting energy
  from the rotor
• Especially for large turbines, the weighted wind
  speed over the rotor is better correlated to the
  turbine power than the simple hub height wind
  speed.
• A new definition for power performance
  measurements is needed.
• FUTURE WORK
• Make power curve measurements using remote
  sensing that covers the whole turbine rotor.
• Extend the simulations over the whole power curve
  using the complete w/t model
• Introduce remote sensing to the standards