Probabilistic surrogates for flow control using combined control strategies

Abstract Wind farm flow control (WFFC) is a promising technology for improving wind operation and design. The presented study focuses on the combination of two most prominent WFFC strategies, yaw-based wake-steering axial induction via constant blade pitch, maximising power production with without load constraint. optimisation performed data-driven polynomial-based probabilistic surrogate models, calibrated through range LES aeroelastic simulations 2-turbine setup. results indicate to be driving mechanism increase production, particularly when loads are not considered. However, seen beneficial alleviation, especially in close spacings. Overall, analyses highlight potential combined strategies safety-critical system provides approach multi-objective control.