13 citations as recorded by crossref.

1. Wind farm flow control: prospects and challenges J. Meyers et al. 10.5194/wes-7-2271-2022
2. Evaluation of the “fan scan” based on three combined nacelle lidars for advanced wind field characterisation P. Meyer & J. Gottschall 10.1088/1742-6596/2265/2/022107
3. Dynamic wake tracking based on wind turbine rotor loads and Kalman filtering D. Onnen et al. 10.1088/1742-6596/2265/2/022024
4. Design, steady performance and wake characterization of a scaled wind turbine with pitch, torque and yaw actuation E. Nanos et al. 10.5194/wes-7-1263-2022
5. Towards the multi-scale Kalman filtering of dynamic wake models: observing turbulent fluctuations and wake meandering R. Braunbehrens et al. 10.1088/1742-6596/2505/1/012044
6. Wind inflow observation from load harmonics: initial steps towards a field validation M. Bertelè et al. 10.5194/wes-6-759-2021
7. Virtual sensors for wind turbines with machine learning‐based time series models N. Dimitrov & T. Göçmen 10.1002/we.2762
8. Wind vane correction during yaw misalignment for horizontal-axis wind turbines A. Rott et al. 10.5194/wes-8-1755-2023
9. Wind Tunnel Testing of Yaw by Individual Pitch Control Applied to Wake Steering F. Campagnolo et al. 10.3389/fenrg.2022.883889
10. LQ Optimal Control for Power Tracking Operation of Wind Turbines A. Grapentin et al. 10.1016/j.ifacol.2023.10.1374
11. Wind farm flow control oriented to electricity markets and grid integration: Initial perspective analysis I. Eguinoa et al. 10.1002/adc2.80
12. The wind farm as a sensor: learning and explaining orographic and plant-induced flow heterogeneities from operational data R. Braunbehrens et al. 10.5194/wes-8-691-2023
13. Wind inflow observation from load harmonics via neural networks: A simulation and field study K. Kim et al. 10.1016/j.renene.2022.12.051