LIDAR-assisted nonlinear output regulation of wind turbines for fatigue load reduction

Abstract. Optimizing wind turbine performance involves maximizing or regulating power generation while minimizing fatigue load on the tower structure, blades, and rotor. In this article, we explore the application of a novel turbine control methodology known as nonlinear output regulation (NOR) for improving turbine control performance. NOR uses a multiple-input-multiple-output design approach to regulate rotor speed and power generation with the generator torque and blade pitch angles, in a unified manner across partial and full load operation. Regulation is achieved using an estimate of rotor-effective wind speed. We consider estimation based on the turbine's SCADA, in particular the Immersion & Invariance (I&I) estimator, as well as LIDAR. We propose to average these two signals to obtain a low-variation real-time estimate of current wind speed.

The performance of the NOR controller is compared against a state-of-the-art baseline reference controller, known as ROSCO. Extensive simulations of the NOR and ROSCO controllers using openFAST on an IEA 15-MW reference turbine, across a broad range of wind speeds in both partial load and full load operating regions are conducted. Results show that NOR with the combination of I&I and LIDAR improves on all considered performance metrics. Lifetime damage-equivalent loads are reduced on the tower by 2.6 % fore-aft and 11.6 % side-to-side, on the blades by 4.7 % flapwise and on the main shaft by 15.2 %. Furthermore, pitch rate is reduced by 22.6 %. The reductions are achieved without sacrificing power generation or tracking performance.