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

Bart Matthijs Doekemeijer, Eric Simley and Paul Fleming
Additional contact information
Bart Matthijs Doekemeijer: National Wind Technology Center, National Renewable Energy Laboratory, 19001 W 119th Ave, Arvada, CO 80007, USA
Eric Simley: National Wind Technology Center, National Renewable Energy Laboratory, 19001 W 119th Ave, Arvada, CO 80007, USA
Paul Fleming: National Wind Technology Center, National Renewable Energy Laboratory, 19001 W 119th Ave, Arvada, CO 80007, USA

Energies, 2022, vol. 15, issue 6, 1-23

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 σ w d = 3 ° in our Gaussian model. First, we demonstrate the non-uniqueness issue of I ∞ and σ w d , 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.

Keywords: FLORIS; model validation; model comparison; offshore wind; wake steering; SCADA; historical data; energy ratio; data post-processing; data analysis (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
https://www.mdpi.com/1996-1073/15/6/1964/pdf (application/pdf)
https://www.mdpi.com/1996-1073/15/6/1964/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jeners:v:15:y:2022:i:6:p:1964-:d:766525

Access Statistics for this article

Energies is currently edited by Ms. Agatha Cao

More articles in Energies from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().