Journal cover Journal topic
Wind Energy Science The interactive open-access journal of the European Academy of Wind Energy
https://doi.org/10.5194/wes-2016-60
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
Research articles
03 Feb 2017
Review status
A revision of this discussion paper is under review for the journal Wind Energy Science (WES).
An analysis of offshore wind farm SCADA measurements to identify key parameters influencing the magnitude of wake effects
Niko Mittelmeier1, Julian Allin1, Tomas Blodau1, Davide Trabucchi2, Gerald Steinfeld2, Andreas Rott2, and Martin Kühn2 1Senvion GmbH, Überseering 10, 22297 Hamburg, Germany
2ForWind – University of Oldenburg, Institute of Physics, Küpkersweg 70, 26129 Oldenburg
Abstract. Atmospheric conditions have a clear influence on wake effects. Stability classification is usually based on wind speed, turbulence intensity, shear and temperature gradients measured partly at met masts, buoys or LiDARs. The objective of this paper is to find a classification for stability based on wind turbine Supervisory Control and Data Acquisition (SCADA) measurements in order to fit engineering wake models better to the current ambient conditions. Two offshore wind farms with met masts have been used to establish a correlation between met mast stability classification and new aggregated artificial signals. The significance of these new signals on power production is demonstrated for two wind farms with met masts and measurements from a long range LiDAR and validated against data from one further wind farm without a met mast. We found a good correlation between the standard deviation of active power divided by the average power of wind turbines in free flow with the ambient turbulence intensity when the wind turbines were operating in partial load. The proposed signal is very sensitive to increased turbulence due to neighbouring turbines and wind farms even at a distance of more than 38 rotor diameters away. It allows to distinguish between conditions with different magnitude of wake effects.

Citation: Mittelmeier, N., Allin, J., Blodau, T., Trabucchi, D., Steinfeld, G., Rott, A., and Kühn, M.: An analysis of offshore wind farm SCADA measurements to identify key parameters influencing the magnitude of wake effects, Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2016-60, in review, 2017.
Niko Mittelmeier et al.
Niko Mittelmeier et al.
Niko Mittelmeier et al.

Viewed

Total article views: 229 (including HTML, PDF, and XML)

HTML PDF XML Total BibTeX EndNote
173 49 7 229 7 4

Views and downloads (calculated since 03 Feb 2017)

Cumulative views and downloads (calculated since 03 Feb 2017)

Viewed (geographical distribution)

Total article views: 229 (including HTML, PDF, and XML)

Thereof 229 with geography defined and 0 with unknown origin.

Country # Views %
  • 1

Saved

Discussed

Latest update: 24 Jun 2017
Publications Copernicus
Download
Short summary
Stability classification is usually based on measurements from met masts, buoys or LiDARs. The objective of this paper is to find a classification for stability based on wind turbine Supervisory Control and Data Acquisition measurements in order to fit engineering wake models better to the current ambient conditions. The proposed signal is very sensitive to increased turbulence. It allows to distinguish between conditions with different magnitude of wake effects.
Stability classification is usually based on measurements from met masts, buoys or LiDARs. The...
Share