Wind turbine load reduction by rejecting the periodic load disturbances

(2014). Subspace predictive repetitive control to mitigate periodic loads on large scale wind turbines. Mechatronics, 24(8), 916-925. DOI: 10.1016/j.mechatronics.2014 General rights Copyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights.• Users may download and print one copy of any publication from the public portal for the purpose of private study or research.• You may not further distribute the material or use it for any profit-making activity or commercial gain • You may freely distribute the URL identifying the publication in the public portal ? Take down policyIf you believe that this document breaches copyright please contact us providing details, and we will remove access to the work immediately and investigate your claim. a b s t r a c tManufacturing and maintenance costs arising out of wind turbine dynamic loading are one of the largest bottlenecks in the roll-out of wind energy. Individual Pitch Control (IPC) is being researched for cost reduction through load alleviation; it poses a challenging mechatronic problem due to its multi-input, multi-output (MIMO) nature and actuation constraints related to the wear of pitch bearings. To address these issues, Subspace Predictive Repetitive Control (SPRC), a novel repetitive control strategy based on the subspace identification paradigm, is presented. First, the Markov parameters of the system are identified online in a recursive manner. These parameters are used to build up the lifted matrices needed to predict the output over the next period. From these matrices an adaptive repetitive control law is derived.To account for actuator limitations, the known shape of wind-induced disturbances is exploited to perform repetitive control in a reduced-dimension basis function subspace. The SPRC methodology is implemented on a high-fidelity numerical aeroelastic environment for wind turbines. Load reductions are achieved similar to those obtained with classical IPC approaches, while considerably limiting the frequency content of the actuator signals.

show abstract

“…A wind turbine can be approximated by a discrete-time LTI (linear, time-invariant) system with unknown periodic disturbances [10]:…”

Section: Step 1: System Definition and Predictor Formulationmentioning

confidence: 99%

“…For the current application, model-based RC has been simulated in [10], specifically to target all periodic loads with a single control loop. It can easily deal with the MIMO problem with a transparent LQR formulation.…”

mentioning

confidence: 99%

Subspace predictive repetitive control to mitigate periodic loads on large scale wind turbines

et al. 2014

Self Cite

View full text Add to dashboard Cite

show abstract

“…In the past decade, research has been conducted on developing load-reducing controllers that "learn" the optimal controller settings online Houtzager et al, 2013;Navalkar et al, 2014Xiao et al, 2016). These controllers are typically scheduled on basis functions and thereby mainly target the periodic wind turbine loading.…”

Section: Introductionmentioning

confidence: 99%

Iterative feedback tuning of wind turbine controllers

2017

View full text Add to dashboard Cite

Abstract. Traditionally, wind turbine controllers are designed using first principles or linearized or identified models. The aim of this paper is to show that with an automated, online, and model-free tuning strategy, wind turbine control performance can be significantly increased. For this purpose, iterative feedback tuning (IFT) is applied to two different turbine controllers: drivetrain damping and collective pitch control. The results, obtained by high-fidelity simulations using the NREL 5MW wind turbine, indicate significant performance improvements over baseline controllers, which were designed using classical loop-shaping techniques. It is concluded that iterative feedback tuning of turbine controllers has the potential to become a valuable tool to improve wind turbine performance.

show abstract

“…The classic LQ formulation is modified to handle periodic disturbance rejection [25]. An important contribution to the load variation on a wind turbine blade has in fact a deterministic periodic nature [26,27]: constant or slow varying sources of disturbances (as gravity, tower shadow, tilt, wind shear, yaw misalignment) produce on the rotating blade load variations with marked periodic components, which depend on the blade azimuthal position and occur at every rotor revolution. Knowledge of the periodic, and hence predictable, disturbances is exploited in the control algorithm, which anticipates, and try to compensate for, the load variations caused by the periodic components.…”

Section: Introductionmentioning

confidence: 99%

A smart rotor configuration with linear quadratic control of adaptive trailing edge flaps for active load alleviation

Bergami

Poulsen

2014

Wind Energy

View full text Add to dashboard Cite

The paper proposes a smart rotor configuration where Adaptive Trailing Edge Flaps (ATEF) are employed for active alleviations of the aerodynamic loads on the blades of the NREL 5 MW reference turbine. The flaps extend for 20 % of the blade length, and are controlled by a Linear Quadratic (LQ) algorithm based on measurements of the blade root flapwise bending moment. The control algorithm includes frequency weighting to discourage flap activity at frequencies higher than 0.5 Hz. The linear model required by the LQ algorithm is obtained from subspace system identification; periodic disturbance signals described by simple functions of the blade azimuthal position are included in the identification to avoid biases from the periodic load variations observed on a rotating blade. The LQ controller uses the same periodic disturbance signals to handle anticipation of the loads periodic component.The effects of active flap control are assessed with aeroelastic simulations of the turbine in normal operation conditions, as prescribed by the IEC standard. The turbine lifetime fatigue damage equivalent loads provide a convenient summary of the results achieved with ATEF control: a 10 % reduction of the blade root flapwise bending moment is reported in the simplest control configuration, whereas reductions of approximately 14 % are achieved by including periodic loads anticipation. The simulations also highlight impacts on the fatigue damage loads in other parts of the structure, in particular, an increase of the blade torsion moment, and a reduction of the tower fore-aft loads.

show abstract

Wind turbine load reduction by rejecting the periodic load disturbances

Cited by 53 publications

References 31 publications

Subspace predictive repetitive control to mitigate periodic loads on large scale wind turbines

Subspace predictive repetitive control to mitigate periodic loads on large scale wind turbines

Iterative feedback tuning of wind turbine controllers

A smart rotor configuration with linear quadratic control of adaptive trailing edge flaps for active load alleviation

Contact Info

Product

Resources

About