Infopack #2 - Location-agnostic and control-oriented load surrogate models

efficient yet accurate load surrogate models are essential to enable fast estimation of fatigue loads on wind turbines, supporting load-aware applications in the control room of the future within SUDoco. These models predict Damage equivalent Loads (DeLs) at any turbine location using local inflow conditions and control settings. Location-agnostic and control-oriented surrogate methods were developed and validated, ensuring applicability across different turbine positions within a wind farm while explicitly accounting for control setpoints. a key challenge was selecting inputs to the surrogate that remain simple enough yet rich enough to capture the nonlinear behaviour of turbine loads. results show that a finite level of input complexity is sufficient to achieve converged and reliable performance for generalised wind turbine load surrogate models. Independent farm-level validation shows a root mean square percentage error (RMSPE) below 4% for all load channels.