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Wind Energy Science The interactive open-access journal of the European Academy of Wind Energy
https://doi.org/10.5194/wes-2017-37
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 4.0 License.
Research articles
27 Sep 2017
Review status
This discussion paper is a preprint. A revision of the manuscript is under review for the journal Wind Energy Science (WES).
On wake modeling, wind-farm gradients and AEP predictions at the Anholt wind farm
Alfredo Peña, Kurt Schaldemose Hansen, Søren Ott, and Maarten Paul van der Laan DTU Wind Energy, Technical University of Denmark, Roskilde, Denmark
Abstract. We investigate wake effects at the Anholt offshore wind farm in Denmark. We perform the analysis with three commonly-used wake models; two engineering approaches (the Park and G. C. Larsen models) and a linearized Reynolds-averaged Navier-Stokes approach (Fuga). From analysis of SCADA and mesoscale model simulations, we show that for westerly flow in particular, there is a clear horizontal wind-speed gradient over the wind farm, which results from the effect of the land nearby. We also show that for annual energy production estimates, in which a wake model is run with inflow conditions derived from mesoscale model outputs, accounting for the horizontal wind-speed gradient gives nearly the same results as averaging all the wake-free wind climates at the turbines' positions or using the wind climate of a position in the middle of the wind farm. However, annual energy production estimates can largely differ when using wind climates that are strongly influenced by the wind-speed gradient. When looking at westerly flow wake cases, where the impact of the wind-speed gradient is largest, the wake models agree with the SCADA fairly well; when looking at a southerly flow case, where the wake losses are highest, they tend to underestimate the wake loss. With the mesoscale-wake model setup, we are also able to estimate the capacity factor of the wind farm rather well when compared to that derived from the SCADA. Finally, we estimate the uncertainty of the wake models and some of its variants by bootstrapping the SCADA. The models tend to underestimate the wake losses and the engineering wake models are as uncertain as Fuga. These results are specific for this wind farm, the available dataset, and the derived inflow conditions.

Citation: Peña, A., Schaldemose Hansen, K., Ott, S., and van der Laan, M. P.: On wake modeling, wind-farm gradients and AEP predictions at the Anholt wind farm, Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2017-37, in review, 2017.
Alfredo Peña et al.
Alfredo Peña et al.
Alfredo Peña et al.

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Short summary
We analyse the wake of the Anholt offshore wind farm in Denmark by intercomparing models and measurements. We also look at the effect of the land on the wind farm by intercomparing mesoscale winds and measurements. Annual energy production and capacity factor estimates are performed using different approaches. Lastly, the uncertainty of the wake models is determined by bootstrapping the data; we find that the wake models generally underestimate the wake losses.
We analyse the wake of the Anholt offshore wind farm in Denmark by intercomparing models and...
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