15 citations as recorded by crossref.

1. Wind farm supervisory controller design for power optimization in localized areas using adaptive learning game theory (ALGT) V. Fazlollahi et al. 10.1177/0309524X231199432
2. Adjoint-based model predictive control for optimal energy extraction in waked wind farms M. Vali et al. 10.1016/j.conengprac.2018.11.005
3. Model‐free closed‐loop wind farm control using reinforcement learning with recursive least squares J. Liew et al. 10.1002/we.2852
4. Stochastic Dynamical Modeling of Wind Farm Turbulence A. Bhatt et al. 10.3390/en16196908
5. IEA Wind Task 32: Wind Lidar Identifying and Mitigating Barriers to the Adoption of Wind Lidar A. Clifton et al. 10.3390/rs10030406
6. A control-oriented dynamic wind farm model: WFSim S. Boersma et al. 10.5194/wes-3-75-2018
7. Wind turbine load validation in wakes using wind field reconstruction techniques and nacelle lidar wind retrievals D. Conti et al. 10.5194/wes-6-841-2021
8. Wake detection in the turbine inflow using nacelle lidars D. Held et al. 10.1088/1742-6596/1102/1/012005
9. Turbulence and Control of Wind Farms C. Shapiro et al. 10.1146/annurev-control-070221-114032
10. Wind farm flow control: prospects and challenges J. Meyers et al. 10.5194/wes-7-2271-2022
11. Field Validation of Wake Steering Control with Wind Direction Variability E. Simley et al. 10.1088/1742-6596/1452/1/012012
12. Robust wake steering control design in a wind farm for power optimisation using adaptive learning game theory (ALGT) method V. Fazlollahi et al. 10.1080/00207179.2021.2009558
13. Dynamic wake tracking based on wind turbine rotor loads and Kalman filtering D. Onnen et al. 10.1088/1742-6596/2265/2/022024
14. Characterization of wind turbine flow through nacelle-mounted lidars: a review S. Letizia et al. 10.3389/fmech.2023.1261017
15. Full-Scale Field Test of Wake Steering P. Fleming et al. 10.1088/1742-6596/854/1/012013