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Siemens Wind Power

Siemens Wind Power. EWEC 2006. Noise Optimization of a Multi-Megawatt Wind Turbine Aero-acoustic noise measurements of an SWT-2.3-93 Aero-acoustic noise calculations of an SWT-2.3-93 and comparison with measurements Posibilities for low-noise power production Conclusions.

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Siemens Wind Power

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  1. Siemens Wind Power

  2. EWEC 2006 Noise Optimization of a Multi-Megawatt Wind Turbine • Aero-acoustic noise measurements of an SWT-2.3-93 • Aero-acoustic noise calculations of an SWT-2.3-93 and comparison with measurements • Posibilities for low-noise power production • Conclusions

  3. Aero-acoustic noise meassurements of an SWT-2.3-93 Aerial view of Høvsøre National Test-site for large prototype wind turbines SWT-2.3-93

  4. Aero-acoustic noise meassurements of an SWT-2.3-93 Turbine Turbine rated power: 2300kW Blade length: 45m Control system: Variable speed, pitch control Tower height: 80m Acoustic noise recording and processing Hardware: Brüel & Kjær Software: Brüel & Kjær (Pulse) Measurement location: On ground 100m downwind of rotor Temporal resolution of averages: 10s bins Frequency resolution of averages: 1/12 octave spectra Turbine data logging (pow, pitch, rpm, wind etc): Full inclusion in noise recording

  5. Aero-acoustic noise meassurements of an SWT-2.3-93 The acoustic data was recorded during 2 consecutive days in may 2006. Approximately 11hrs of data 3D data matrix to populate with recordings 1st dimension: Wind: 4 to 12 m/s 2nd dimension: Pitch: -4 to 12 degrees 3rd dimension: Rotor speed: 9-18rpm Post-processing details of 10s binned 1/12 octave spectra Background noise subtraction High frequency bird noise identification and subtraction

  6. Aero-acoustic noise meassurements of an SWT-2.3-93

  7. Aero-acoustic noise meassurements of an SWT-2.3-93 Note: High rotor-speed sensitivity, less pitch sensitivity and very litle wind sensitivity on acoustics

  8. Aero-acoustic noise calculations of an SWT-2.3-93 • The aero-acoustic source model • 5 types of noise: • TE bluntness vortex shedding (BPM model) • Laminar boundary layer TE vortex shedding (BPM model) • Turbulent boundary layer TE (BPM model) • Turbulent boundary layer separation (BPM model) • Turbulent inflow (Amiet model with simplified Guidati) • Model implementation: NAFNoise (Moriarty, NREL) • Boundary layer inputs: XFoil (Drela, MIT).

  9. Aero-acoustic noise calculations of an SWT-2.3-93 • The aero-acoustic propagation model • Modifications to simple radial propagation from a point source: • Rotor distributed sources • Directivity (blade acts an acoustic dipole) • Air absorption • Atmospheric shear correction • Doppler shift • Absent modifications: • Non-flat terrain • Multiple sound ray reflections due to shear

  10. Aero-acoustic noise calculations of an SWT-2.3-93 Superposition of calculated soundpower contours at 8m/s

  11. Aero-acoustic noise calculations of an SWT-2.3-93 Spectral comparisons at low rotor-speed:

  12. Aero-acoustic noise calculations of an SWT-2.3-93 Spectral comparisons at high rotor-speed:

  13. Posibilities for low-noise power production

  14. Posibilities for low-noise power production Aero-acoustic low-noise analysis Max. sound emission at 11m/s, just before rated power is reached. Low-noise power production is aimed at the operation point at 11m/s hub height wind. Quick ‘n dirty gradient analysis Pitch variation: -1.05 dB/deg, -0.2 %AEP/dB, 0.0 %flapload/dB maxRPM variation: 0.72 dB/rpm, -0.5 %AEP/dB, -1.5 %flapload/dB Chord variation: -0.03 dB/(%chord) 2.5 %AEP/dB, 28 %flapload/dB Blade thickness variation: -0.02 dB/(%thick), -8.4 %AEP/dB, 4.5 %flapload/dB

  15. Conclusions and future work Acoustic model validation • Turbulent boundary layer separation noise is qualitatively well reproduced by model, but is overpredicted. Rotational 3D-effect that postpones stall might be part of theexplanation. • TE bluntness model overpredicts measurements by 5+ dBs, hence excluded. • Turbulent boundary layer TE noise model fits measurements well. • Turbulent inflow noise model generally fits measured low frequencies well. Low-noise turbine operation • Positive pitching (away from stall) is the primary handle according to model – however, measurements indicate much less pitch sensitivity. Reduced RPM also reduces noise at a low cost according to both model and measurements. • Chord- and thickness-variations do not show significant impact on acoustics, and AEP- and/or load-cost is significant. • Every dB-favorable change has a cost, either on AEP or loads. Overall the model can deliver accurate predictions, once the deficiencies (bluntness) and weaknesses (separation noise) are identified. It will assist future blade design.

  16. Thankyou for your attention

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