Comparison of the Gaussian Wind Farm Model with Historical Data of Three Offshore Wind Farms

Bart Doekemeijer, Eric Simley, Paul Fleming

Research output: Contribution to journalArticlepeer-review

12 Scopus Citations


A recent expert elicitation showed that model validation remains one of the largest barriers for commercial wind farm control deployment. The Gaussian-shaped wake deficit model has grown in popularity in wind farm field experiments, yet its validation for larger farms and throughout annual operation remains limited. This article addresses this scientific gap, providing a model comparison of the Gaussian wind farm model with historical data of three offshore wind farms. The energy ratio is used to quantify the model’s accuracy. We assume a fixed turbulence intensity of I = 6% and a standard deviation on the inflow wind direction of σwd = 3 in our Gaussian model. First, we demonstrate the non-uniqueness issue of I and σwd, which display a waterbed effect when considering the energy ratios. Second, we show excellent agreement between the Gaussian model and historical data for most wind directions in the Offshore Windpark Egmond aan Zee (OWEZ) and Westermost Rough wind farms (36 and 35 wind turbines, respectively) and wind turbines on the outer edges of the Anholt wind farm (110 turbines). Turbines centrally positioned in the Anholt wind farm show larger model discrepancies, likely due to deep-array effects that are not captured in the model. A second source of discrepancy is hypothesized to be inflow heterogeneity. In future work, the Gaussian wind farm model will be adapted to address those weaknesses.

Original languageAmerican English
Article number1964
Number of pages23
Issue number6
StatePublished - 2022

Bibliographical note

Publisher Copyright:
© 2022 by the authors. Licensee MDPI, Basel, Switzerland.

NREL Publication Number

  • NREL/JA-5000-81375


  • Data analysis
  • Data post-processing
  • Energy ratio
  • Historical data
  • Model comparison
  • Model validation
  • Offshore wind
  • Wake steering


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