Erlangen 2018 – wissenschaftliches Programm
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AKE: Arbeitskreis Energie
AKE 7: Wind Energy
AKE 7.2: Vortrag
Montag, 5. März 2018, 16:45–17:00, B 0.014
Yaw-angle optimisation of wind farms based on a statistical meandering wake model — Emil Thogersen1, Bo Tranberg1, Jürgen Herp2, and •Martin Greiner1 — 1Department of Engineering, Aarhus University — 2The Maersk Mc-Kinney Moller Institute, University of Southern Denmark
The wake produced by a wind turbine is dynamically meandering and of rather narrow nature. Only when looking at large time averages, the wake appears to be static and rather broad, and is then well described by simple engineering models like the Jensen wake model (JWM). We generalise the latter deterministic models to a statistical meandering wake model (SMWM), where a random directional deflection is assigned to a narrow wake in such a way that on average it resembles a broad Jensen wake. In a second step, the model is further generalised to wind-farm level, where the deflections of the multiple wakes are treated as independently and identically distributed random variables. When carefully calibrated to the Nysted wind farm, the ensemble average of the statistical model produces the same wind-direction dependence of the power efficiency as obtained from the standard Jensen model. Upon using the JWM to perform a yaw-angle optimisation of wind-farm power output, we find an optimisation gain of 6.7% for the Nysted wind farm when compared to zero yaw angles and averaged over all wind directions. When applying the obtained JWM-based optimised yaw angles to the SMWM, the ensemble-averaged gain is calculated to be 7.5%. This outcome indicates the possible operational robustness of an optimised yaw control for real-life wind farms.