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

Journal Article · Tue Mar 08 00:00:00 EST 2022 · Energies

DOI:https://doi.org/10.3390/en15061964· OSTI ID:1855780

Doekemeijer, Bart Matthijs ^[1]; Simley, Eric ^[1]; Fleming, Paul ^[1]

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1. National Renewable Energy Lab. (NREL), Golden, CO (United States)

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 $$σ_{wd}$$ = 3° in our Gaussian model. First, we demonstrate the non-uniqueness issue of $$I_∞$$ and $$σ_{wd}$$, 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.

• Research Organization: National Renewable Energy Laboratory (NREL), Golden, CO (United States)
• Sponsoring Organization: USDOE Office of Energy Efficiency and Renewable Energy (EERE), Renewable Power Office. Wind Energy Technologies Office
• Grant/Contract Number: AC36-08GO28308
• OSTI ID: 1855780
• Report Number(s): NREL/JA-5000-81375; MainId:82148; UUID:328d47bd-41b1-451f-8264-4ea0cf0b36d8; MainAdminID:63775
• Journal Information: Energies, Journal Name: Energies Journal Issue: 6 Vol. 15; ISSN 1996-1073
• Publisher: MDPI
• Country of Publication: United States
• Language: English

Related Subjects

17 WIND ENERGY
FLORIS
SCADA
data analysis
data post-processing
energy ratio
historical data
model comparison
model validation
offshore wind
wake steering