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.
Initial results from a field campaign of wake steering applied at a commercial wind farm–Part 1.Wind Energy Science.2019;4(2):273–285
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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.