Repetitive Individual Pitch Control for Load Alleviation at Variable Rotor Speed

Abstract

In recent years, wind turbines have been growing in size and became more lightweight and thus more flexible. Spatial variation in the wind speed results in asymmetrical blade loads, which include a periodic component increasing with growing wind turbine size. Asymmetrical blade loads can be reduced by individual blade pitch control in general and repetitive control can reduce especially the periodical parts of the loads. We investigate, how a repetitive control based individual blade pitch controller as extension to an existing collective pitch controller can reduce periodical loads resulting from unsteady non-uniform wind conditions under consideration of variable rotor speeds. As plant, we use a simulation model of a 3 MW wind turbine, developed by W2E Wind to Energy GmbH, and control it with a model predictive collective pitch controller. This controller is extended with the proposed repetitive individual pitch control scheme. This study shows, that the presented repetitive controller reduces especially the tower yaw moments by up to 65% and higher harmonics of the blade root moments by up to 30% at the cost of increased pitch activity. Hence, for the use of this controller one has to balance the load reduction of blades and tower with increased loads of the pitch actuators.

A reinforcement‐learning approach for individual pitch control

“…When the TI increases, the stochastic part of the load variations, and hence of the DEL, increases, yet both IPCs have a hard time dealing with these additional fatigue loads. Several contributions in the literature have addressed the challenge of alleviating non‐deterministic loads, like Kallen et al 21 and Bottasso et al, 58 by explicitly designing the controller with two layers: one in charge of the periodical loads and the other focusing on the stochastic ones typically resulting from turbulence. Though the RL‐IPC controller does not have such a two‐layer architecture, it can detect gusts through the sensing module and directly react to them by adapting the pitching amplitude and phase of the blades.…”

“…On the other hand, repetitive control has also been reported due to its ability to deal with periodic signals and track periodic references 20 . Kallen 21 takes advantage of that and uses the information perceived on a blade to anticipatively pass it on to the next blade. Friis 22 used repetitive model predictive control by including a repetitive wind disturbance in the MPC prediction.…”

A Study of a Gain-Scheduled Individual Pitch Controller for an NREL 5 MW Wind Turbine

“…Proportional-integral (PI) controllers are typically used as the tilt and yaw controllers [8], and studies using optimal controllers, robust controllers, and fuzzy controllers have been conducted [13][14][15][16][17]. In addition to the 1P component of the asymmetric moment load acting on the blade, research was also conducted on using additional individual pitch control inputs to reduce higher-order harmonic components above 2P [18][19][20][21]. Just as gain scheduling is applied to compensate for the nonlinearity of the power coefficient in the collective pitch controller [3], gain scheduling can also be applied to compensate for the nonlinearity of the thrust coefficient in the individual pitch controller [21].…”

Assessment of an actuator disk‐based approach for the prediction of fatigue loads in a perspective of wind farm‐scale application

“…It is thus of a crucial importance to deploy efforts in the prediction of the fatigue damage a wind turbine will suffer during its operation, either to optimally design the wind farm or to develop load alleviation strategies that can be used during the wind farm operation. Those strategies encompass load alleviation at a wind turbine level 3–5 but also schemes aiming at ensuring a more uniform and potentially reduced wear and tear of the rotors at a wind farm scale 6,7 …”

“…For some wind turbine subassemblies, the downtime associated with repair may be significant, mainly in the offshore environment: This decreases the wind turbine reliability, directly impacting the Levelized Cost of Energy, as demonstrated in Dao et al 2 It is thus of a crucial importance to deploy efforts in the prediction of the fatigue damage a wind turbine will suffer during its operation, either to optimally design the wind farm or to develop load alleviation strategies that can be used during the wind farm operation. Those strategies encompass load alleviation at a wind turbine level [3][4][5] but also schemes aiming at ensuring a more uniform and potentially reduced wear and tear of the rotors at a wind farm scale. 6,7 As the development of control strategies or the potential arrangement of a future wind farm often relies on numerical studies, it is essential that the simulation tools provide accurate blade/structural loads and fatigue estimates.…”