Journal article Open Access
Online model calibration for a simplified LES model in pursuit of real-time closed-loop wind farm control
Doekemeijer, Bart M;
Boersma, Sjoerd;
Pao, Lucy Y;
Knudsen, Torben;
van Wingerden, Jan-Willem
Wind farm control often relies on computationally inexpensive surrogate models to predict the dynamics inside a farm. However, the reliability of these models over the spectrum of wind farm operation remains questionable due to the many uncertainties in the atmospheric conditions and tough-to-model dynamics at a range of spatial and temporal scales relevant for control. A closed-loop control framework is proposed in which a simplified model is calibrated and used for optimization in real time. This paper presents a joint state-parameter estimation solution with an ensemble Kalman filter at its core, which calibrates the surrogate model to the actual atmospheric conditions. The estimator is tested in high-fidelity simulations of a nine-turbine wind farm. Exclusively using measurements of each turbine’s generated power, the adaptability to modeling errors and mismatches in atmospheric conditions is shown. Convergence is reached within 400 s of operation, after which the estimation error in flow fields is negligible. At a low computational cost of 1.2 s on an 8-core CPU, this algorithm shows comparable accuracy to the state of the art from the literature while being approximately 2 orders of magnitude faster.
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- Publication date:
- October 24, 2018
- DOI:
-
- Keyword(s):
- Wind farm control WFSim closed-loop control kalman filtering estimation wind farm modeling LES wind farm optimization
- Published in:
- Wind Energy Science: 3 pp. 749-765 (2).
- Grants:
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European Commission:
- CL-Windcon - Closed Loop Wind Farm Control (727477)
- License (for files):
- Creative Commons Attribution 4.0 International