Gijs van der Veen

Global Identification of Wind Turbines Using a Hammerstein Identification Method

In this brief, we present a novel methodology to obtain a nonlinear data-driven model of a wind turbine. We have previously shown that the elementary dynamics of wind turbines can be represented in the form of a multivariable closed-loop Hammerstein structure, where the nonlinear mappings consist of the torque and thrust coefficients. Hammerstein systems consist of a static nonlinearity followed by a linear, time-invariant dynamic subsystem. The dynamic subsystem is identified using a new closed-loop subspace method. The nonlinearity is described using a recently developed regression framework for multivariate splines. We further propose a separable least-squares framework for recovery of the low-rank structure between the nonlinearity and the linear time-invariant system. The method is applied to a detailed simulation of the three-bladed NREL controls advanced research turbine.

Closed-loop MOESP subspace model identification with parametrisable disturbances

A new subspace identification method for systems operating either in open-loop or in closed-loop is presented. The method obtains an estimate of the innovation sequence by performing an RQ-factorization of the measurement data, thereby avoiding explicitly solving a least-squares problem. In a second step, the estimated innovation sequence is used to perform ordinary MOESP [1] to find the system matrices up to a similarity transformation. The closed-loop identification algorithm also applies to cases where certain disturbance inputs are present that can be parametrised in terms of suitable basis functions. All computations are performed using orthogonal factorisations of the data. The method is illustrated by applying it to a system operating in closed-loop and to measurements from a real system with periodic disturbances.

Aeroelastic Control Using Distributed Floating Flaps Activated by Piezoelectric Tabs

In this paper, a novel aeroservoelastic effector configuration that is actuated by piezoelectric tabs is presented. The effector exploits trailing-edge tabs installed on free-floating flaps (FFFs). These flaps are used to prevent flutter from occurring and to alleviate loads originating from external excitations such as gusts. A vertical tailplane wind-tunnel model with two free-floating rudders and a flutter control mechanism were designed, and the aeroelastic stability and response characteristics have been modeled numerically. The controller uses the tailplane tip acceleration as a sensor and sends control signals to the piezoelectrically actuated tabs. Wind-tunnel experiments were performed to demonstrate the feasibility of the technology. It was demonstrated experimentally that the flutter speed associated with the free rudders could be increased by 80%. The same controller, applied to the external rudder, was used to alleviate the aeroelastic response of the tailplane to the excitation of the other ...

Gust load alleviation of an unmanned aerial vehicle wing using variable camber

It is vital for an unmanned aerial vehicle to meet contradictory mission requirements originating from different tasks this type of aircraft has to fulfill. The ability to switch between configurations greatly expands the range of possible missions. An unmanned aerial vehicle wing has been developed to demonstrate the capacity to optimize the aerodynamic and structural performances according to the mission stage. The wing is equipped with four macro fiber composite benders that can be controlled individually, and each of these macro fiber composite benders actuates a section of the wing. A numerical study was conducted with XFLR5 to determine the optimal configurations of the flap positions for both range and endurance. A wind tunnel study was performed to verify these results. During the experiment, a maximum attainable increase in lift coefficient of 0.072 could be achieved, while numerically the increase was computed to be 0.079. The wide-frequency bandwidth of the actuators allows using the developed system also for other purposes such as load alleviation. Unmanned aerial vehicles are often light and fly at low airspeeds, which make them very sensitive to gust excitation. For this purpose, the experimental model was equipped with two accelerometers to measure the amplitude of the first two deformation modes. Significant load alleviation capacities with reductions up to 50% in load amplitude could be achieved. This reduction was achieved, even though the wing box contributes largely to the structural damping, as the foam for the construction absorbs a significant proportion of the vibrations.

Data-driven modelling of wind turbines

In this paper we present a novel approach that allows global modelling of the power control dynamics of a wind turbine based on measured data. The approach is based on the assumption that all the nonlinearities over the operating range arise from a static aerodynamic mapping, which is interconnected with linear, time-invariant dynamics. This so called Hammerstein structure is exploited to simplify the model identification procedure. The global model is suited to control design methods such as model predictive control or can be used to extract local linear models. The approach is demonstrated on a benchmark example, the 5MW NREL/Upwind reference turbine and is shown to work well. Tools from convex optimisation and the recently introduced nuclear norm techniques prove to be instrumental to the successful implementation of the algorithms.

Multi-material topology optimization of viscoelastically damped structures using a parametric level set method:

The design of high performance instruments often involves the attenuation of poorly damped resonant modes. Current design practices typically rely on informed trial and error based modifications to improve dynamic performance. In this article, a multi-material topology optimization approach is presented as a systematic methodology to develop structures with optimal damping characteristics. The proposed method applies a multi-material, parametric, level set-based topology optimization to simultaneously distribute structural and viscoelastic material to optimize damping characteristics. The viscoelastic behavior is represented by a complex-valued material modulus resulting in a complex-valued eigenvalue problem. The structural loss factor is used as objective function during the optimization and is calculated using the complex-valued eigenmodes. An adjoint sensitivity analysis is presented that provides an analytical expression for the corresponding sensitivities. Multiple numerical examples are treated to illustrate the effectiveness of the approach and the influence of different viscoelastic material models on the optimized designs is studied. The optimization routine is able to generate designs for a number of eigenmodes and to attenuate a resonant mode of an existing structure.

Field testing a wind turbine drivetrain/tower damper using advanced design and validation techniques

As an ongoing trend, the design of wind turbines is moving towards larger machines with components optimized for cost effectiveness. This leads to very large and flexible structures with lightly damped modes. Good control design is becoming more essential to ensure safe and stable operation over the life of the turbine. Additionally, there is growing interest in expanding the number of sensors and actuators available for closed-loop control. The increasing number of control variables in modern wind turbines will necessitate model-based controller design to handle the complexity of the flexible and coupled control loops in an effective and robust way. Recent literature in wind energy has explored the use of modern control design techniques such as state-space and robust control design methods and closed-loop system identification for model identification. However, this literature is, to date, mostly confined to simulation studies. Field testing is necessary to demonstrate the effectiveness of advanced design and validation techniques in a practical application. In this paper, we design two alternative dampers for the lightly damped drivetrain and tower modes of an experimental turbine. One design is based on classical iterative design approaches, while the other uses an H∞ approach. The two controllers are then validated using two alternative methods: the traditional extended field test and a relatively short system identification experiment. The paper demonstrates that even in this sub-problem of wind turbine control consisting of only two loops, the use of advanced design and validation techniques is very effective at converging quickly to good control designs and quickly assessing their performance.