TY - JOUR
T1 - Launch of the FarmConners Wind Farm Control benchmark for code comparison
AU - Göcmen, Tuhfe
AU - Kölle, Konstanze
AU - Andersen, Soren Juhl
AU - Eguinoa, Irene
AU - Duc, Thomas
AU - Campagnolo, Filippo
AU - Iribas-Latour, Mikel
AU - Astrain, David
AU - Bottasso, Carlo
AU - Meyers, Johan
AU - Van Wingerden, Jan Willem
AU - Giebel, Gregor
N1 - Publisher Copyright:
© 2020 Published under licence by IOP Publishing Ltd.
PY - 2020/9/22
Y1 - 2020/9/22
N2 - Careful validation of the modelling and control actions is of vital importance to build confidence in the value of coordinated wind farm control (WFC). The efficiency of flow models applied to WFC should be evaluated to provide reliable assessment of the performance of WFC. In order to achieve that, FarmConners launches a common benchmark for code comparison to demonstrate the potential benefits of WFC, such as increased power production and mitigation of loads. The benchmark builds on available data sets from previous and ongoing campaigns: synthetic data from high-fidelity simulations, measurements from wind tunnel experiments, and field data from a real wind farm. The participating WFC models are first to be calibrated or trained using normal operation periods. For the blind test, both the axial induction and wake steering control approaches are included in the dataset and to be evaluated through the designed test cases. Three main test cases are specified, addressing the impact of WFC on single full wake, single partial wake, and multiple wake. The WFC model outcomes will be compared during the blind test phase, through power gain and wake loss reduction as well as alleviation of wake-added turbulence intensity and structural loads. The probabilistic validation will be based on the median and quartiles of the observations and WFC model predictions. Every benchmark participant will be involved in the final publication, where the comparison of different tools will be performed using the defined test cases. Instructions on how to participate are also provided on farmconners.readthedocs.io.
AB - Careful validation of the modelling and control actions is of vital importance to build confidence in the value of coordinated wind farm control (WFC). The efficiency of flow models applied to WFC should be evaluated to provide reliable assessment of the performance of WFC. In order to achieve that, FarmConners launches a common benchmark for code comparison to demonstrate the potential benefits of WFC, such as increased power production and mitigation of loads. The benchmark builds on available data sets from previous and ongoing campaigns: synthetic data from high-fidelity simulations, measurements from wind tunnel experiments, and field data from a real wind farm. The participating WFC models are first to be calibrated or trained using normal operation periods. For the blind test, both the axial induction and wake steering control approaches are included in the dataset and to be evaluated through the designed test cases. Three main test cases are specified, addressing the impact of WFC on single full wake, single partial wake, and multiple wake. The WFC model outcomes will be compared during the blind test phase, through power gain and wake loss reduction as well as alleviation of wake-added turbulence intensity and structural loads. The probabilistic validation will be based on the median and quartiles of the observations and WFC model predictions. Every benchmark participant will be involved in the final publication, where the comparison of different tools will be performed using the defined test cases. Instructions on how to participate are also provided on farmconners.readthedocs.io.
UR - http://www.scopus.com/inward/record.url?scp=85092368054&partnerID=8YFLogxK
U2 - 10.1088/1742-6596/1618/2/022040
DO - 10.1088/1742-6596/1618/2/022040
M3 - Conference article
AN - SCOPUS:85092368054
SN - 1742-6588
VL - 1618
JO - Journal of Physics: Conference Series
JF - Journal of Physics: Conference Series
IS - 2
M1 - 022040
T2 - Science of Making Torque from Wind 2020, TORQUE 2020
Y2 - 28 September 2020 through 2 October 2020
ER -