Adrien Guillore - The development of load surrogates models for wind farm control applications

In the last years, Wind Farm Control has started to demonstrate its important potential up to the field implementation and in the industry, mostly for power maximization. But uncertainties remain on the effect of wind farm control on turbine loads, which the scientific community has identified as a further research need. Predicting turbine fatigues, using Damage Equivalent Loads (DELs), require computationally expensive aero-servo-elastic simulations. It is thus not so straightforward to include in real-time "live" control and/or in offline iterative optimizations (for instance in FLORIS optimal-configuration finder). For this reason, the development and the use of load surrogate models is of current interest as it could allow tackling these challenges. This talk will present some methodology that has been recently explored to develop load surrogate models based solely on Rotor-Equivalent Inflow Quantities (REIQs). If it can be shown to be accurate enough, it is believed that using a load surrogate model based only on the individual turbine REIQs would be quite general and universal (not needing to know the turbine position in the wind farm, the presence of an undetected atmospheric effect, or the local terrain specificities....). After generating a reference dataset, Artificial Neural Networks are trained to predict the DELs based on the REIQs, and the prediction capabilities are assessed. Some (promising) preliminary results of the application of this methodology in both a simulation environment (FAST.Farm) and in a wind tunnel experimental environment (using TUM scaled wind turbines) will be presented and discussed.

This work has been done collaboratively with Dr. Filippo Campagnolo, and Prof. Carlo Bottasso, from TUM as well.