Detecting abnormal small-scale events by nacelle lidar at the AD8-180 prototype turbine

Abstract

Abstract Identifying anomalous wind events that lead to high aerodynamic loads is essential for mitigating extreme loading on wind turbines. Building upon a recently published method, we herein introduce an extended methodology for early small-scale abnormal wind event detection employing a pulsed nacelle-lidar, potentially triggering preemptive control actions within the wind turbine system. The extended method integrates the consideration of multiple measurement ranges within the induction zone and the evaluation of a horizontally asymmetric wind detection parametrized through a difference in lidar line-of-sight (LoS) measurements. A comparative assessment of various detection algorithms is conducted, leading to the identification of optimal parameter configurations and an evaluation of their reliability. With the proposed methodology, the false positive rate can be reduced with respect to the original methodology, although not all extreme loading events are detected.