An analysis of offshore wind farm SCADA measurements to identify key parameters influencing the magnitude of wake effects

The Science of Making Torque from Wind

Mittelmeier, N.^1 ; Blodau, T.^1 ; Steinfeld, G.^2 ; Rott, A.^2 ; Kühn, M.^2

Senvion GmbH, Überseering 10, Hamburg

22297, Germany^1

University of Oldenburg, Ammerländer Heerstraße 136, Oldenburg

26129, Germany^2

关键词: Ambient conditions;    Atmospheric conditions;    Multiple measurements;    SCADA measurements;    Stability classification;    Standard deviation;    Supervisory control and data acquisition;    Turbulence intensity;   

Others  :  https://iopscience.iop.org/article/10.1088/1742-6596/753/3/032052/pdf
DOI  :  10.1088/1742-6596/753/3/032052

来源: IOP

【 摘 要 】

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 statistical signals based on multiple measurement devices. The significance of these new signals on power production is demonstrated for two wind farms with met masts 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.