Four analytical wake models are tested against field measurements from Lillgrund, reproducing wake trends with normalised velocity deficit MAE of 7-15% and power errors up to 30% at farm level.
An alternative form of the super-Gaussian wind turbine wake model.Wind Energy Science Discussions.2020;2020:1–16
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Assessing engineering wake models against operational data: insights from the Lillgrund wind farm wake steering campaign
Four analytical wake models are tested against field measurements from Lillgrund, reproducing wake trends with normalised velocity deficit MAE of 7-15% and power errors up to 30% at farm level.