9 citations as recorded by crossref.

1. Uncovering wind power forecasting uncertainty sources and their propagation through the whole modelling chain J. Yan et al. 10.1016/j.rser.2022.112519
2. Model‐free closed‐loop wind farm control using reinforcement learning with recursive least squares J. Liew et al. 10.1002/we.2852
3. Streaming dynamic mode decomposition for short‐term forecasting in wind farms J. Liew et al. 10.1002/we.2694
4. Data-driven wind farm flow control and challenges towards field implementation: A review T. Göçmen et al. 10.1016/j.rser.2025.115605
5. Probabilistic surrogates for flow control using combined control strategies C. Debusscher et al. 10.1088/1742-6596/2265/3/032110
6. Virtual sensors for wind turbines with machine learning‐based time series models N. Dimitrov & T. Göçmen 10.1002/we.2762
7. Enhanced Modeling of Joint Yaw and Axial Induction Control Using Blade Element Momentum Methods J. Liew et al. 10.1088/1742-6596/2767/3/032018
8. Robust wind turbine monitoring for digital twin integration: A physics-informed covariance-preserving deep learning approach M. Ko & A. Shafieezadeh 10.1016/j.renene.2025.123176
9. Increasing the Accuracy of Hourly Multi-Output Solar Power Forecast with Physics-Informed Machine Learning D. Pombo et al. 10.3390/s22030749