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A new RANS-based wind farm parameterization and inflow model for wind farm cluster modeling

Authors :
M. P. van der Laan
O. García-Santiago
M. Kelly
A. Meyer Forsting
C. Dubreuil-Boisclair
K. Sponheim Seim
M. Imberger
A. Peña
N. N. Sørensen
P.-E. Réthoré
Source :
Wind Energy Science, Vol 8, Pp 819-848 (2023)
Publication Year :
2023
Publisher :
Copernicus Publications, 2023.

Abstract

Offshore wind farms are more commonly installed in wind farm clusters, where wind farm interaction can lead to energy losses; hence, there is a need for numerical models that can properly simulate wind farm interaction. This work proposes a Reynolds-averaged Navier–Stokes (RANS) method to efficiently simulate the effect of neighboring wind farms on wind farm power and annual energy production. First, a novel steady-state atmospheric inflow is proposed and tested for the application of RANS simulations of large wind farms. Second, a RANS-based wind farm parameterization is introduced, the actuator wind farm (AWF) model, which represents the wind farm as a forest canopy and allows to use of coarser grids compared to modeling all wind turbines as actuator disks (ADs). When the horizontal resolution of the RANS-AWF model is increased, the model results approach the results of the RANS-AD model. A double wind farm case is simulated with RANS to show that replacing an upstream wind farm with an AWF model only causes a deviation of less than 1 % in terms of the wind farm power of the downstream wind farm. Most importantly, a reduction in CPU hours of 75.1 % is achieved, provided that the AWF inputs are known, namely, wind farm thrust and power coefficients. The reduction in CPU hours is further reduced when all wind farms are represented by AWF models, namely, 92.3 % and 99.9 % for the double wind farm case and for a wind farm cluster case consisting of three wind farms, respectively. If the wind farm thrust and power coefficient inputs are derived from RANS-AD simulations, then the CPU time reduction is still 82.7 % for the wind farm cluster case. For the double wind farm case, the RANS models predict different wind speed flow fields compared to output from simulations performed with the mesoscale Weather Research and Forecasting model, but the models are in agreement with the inflow wind speed of the downstream wind farm. The RANS-AD-AWF model is also validated with measurements in terms of wind farm wake shape; the model captures the trend of the measurements for a wide range of wind directions, although the measurements indicate more pronounced wind farm wake shapes for certain wind directions.

Subjects

Subjects :
Renewable energy sources
TJ807-830

Details

Language :
English
ISSN :
23667443 and 23667451
Volume :
8
Database :
Directory of Open Access Journals
Journal :
Wind Energy Science
Publication Type :
Academic Journal
Accession number :
edsdoj.424f8cb0e55b4d85b2a1e79344de26cc
Document Type :
article
Full Text :
https://doi.org/10.5194/wes-8-819-2023