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Wind Turbine Geometrical and Operation Variables Reconstruction from Blade Acceleration Measurements

Author

Listed:
  • Francisco Pimenta

    (Faculty of Engineering, University of Porto, 4200-465 Porto, Portugal)

  • Carlos Moutinho

    (Faculty of Engineering, University of Porto, 4200-465 Porto, Portugal)

  • Filipe Magalhães

    (Faculty of Engineering, University of Porto, 4200-465 Porto, Portugal)

Abstract

To develop reliable numerical models and better interpret monitoring campaigns experimental data of wind turbines, knowing the structure operation conditions, in particular the rotor angular velocity and blades’ pitch angle, is of paramount importance, but often not known due to confidentiality restrictions, or known with low time resolution (typically 10 min average values). In this work, it is shown analytically that blades accelerations measurements contain valuable information that allow for a better characterisation of the effective rotor shaft tilt and blades cone angle for different operating conditions. It is also shown that these measurements can be used to reconstruct the time history of the rotor angular velocity and blades’ pitch angle. After presented in an analytical framework, the methodology is validated with experimental data of two full scale wind turbines. The successful reconstruction of the rotor operating conditions shows that the method presented can be used to provide further insight into the dynamics of the structure that aids monitoring data analysis and provides an alternative method to monitor the SCADA systems themselves. The paper combines quite unique experimental data collected at two operating rotors with original data processing strategies that provide very valuable information to researchers and wind turbine operators.

Suggested Citation

  • Francisco Pimenta & Carlos Moutinho & Filipe Magalhães, 2023. "Wind Turbine Geometrical and Operation Variables Reconstruction from Blade Acceleration Measurements," Energies, MDPI, vol. 17(1), pages 1-13, December.
  • Handle: RePEc:gam:jeners:v:17:y:2023:i:1:p:229-:d:1311495
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