2556513
doi
10.5281/zenodo.2556513
oai:zenodo.org:2556513
Boersma, Sjoerd
Delft University of Technology
Pao, Lucy Y
University of Colorado Boulder
van Wingerden, Jan-Willem
Delft University of Technology
Joint state-parameter estimation for a control-oriented LES wind farm model
Doekemeijer, Bart M
Delft University of Technology
info:eu-repo/semantics/openAccess
Creative Commons Attribution Non Commercial Share Alike 3.0 Unported
https://creativecommons.org/licenses/by-nc-sa/3.0/legalcode
wind farm control
state estimation
closed-loop
kalman filtering
<p>Wind farm control research typically relies on computationally inexpensive, surrogate models for real-time optimization. However, due to the large time delays involved, changing atmospheric conditions and tough-to-model flow and turbine dynamics, these surrogate models need constant calibration. In this paper, a novel real-time (joint state-parameter) estimation solution for a medium-fidelity dynamical wind farm model is presented. In this work, we demonstrate the estimation of the freestream wind speed, local turbulence, and local wind field in a two-turbine wind farm using exclusively turbine power measurements. The estimator employs an Ensemble Kalman filter with a low computational cost of approximately 1.0 s per timestep on a dual-core notebook CPU. This work presents an essential building block for real-time wind farm control using computationally efficient dynamical wind farm models.</p>
Zenodo
2018-08-03
info:eu-repo/semantics/conferencePaper
2556512
final
award_title=Closed Loop Wind Farm Control; award_number=727477; award_identifiers_scheme=url; award_identifiers_identifier=https://cordis.europa.eu/projects/727477; funder_id=00k4n6c32; funder_name=European Commission;
1579541809.449531
1115671
md5:3749c456c84d56b6e75bc5078cd88c64
https://zenodo.org/records/2556513/files/20180308_TORQUE_Doekemeijer_final.pdf
public
10.5281/zenodo.2556512
isVersionOf
doi