Abstract
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.
Highlights
The commercial interest in wind farm control is growing substantially
The FLORIS predictions with heterogeneous inflow are better in a few situations, near wind directions of 80◦ and 200◦, yet are mostly equal to the predictions with homogeneous inflows
The predicted energy ratios significantly diverge from the historical data for wind directions less than 50◦ and greater than 330◦
Summary
The commercial interest in wind farm control is growing substantially. one leading wind turbine manufacturer already provides a wake-steering solution to its customers [1], other original equipment manufacturers and wind farm owners have not yet commercialized the concept. The authors use the simplified wind farm flow model from Bastankhah and Porté-Agel [33] They show reasonable agreement between their model and field measurements for the wake locations, yet the wake depth shows significant discrepancies. In non-wake-steering operation, the GCH model falls back to the Gaussian wind farm flow model by Bastankhah and Porté-Agel [33] This wake deficit model was initially calibrated through wind tunnel measurements in the original article [33], and has since received limited validation in comparison to historical data in the literature. There has been a significant lack of the inclusion of inflow and measurement uncertainty in the validation of engineering models This article bridges these gaps by comparing the Gaussian wind farm flow model from Bastankhah and Porté-Agel [33] to historical data of three large offshore wind farms.
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