Extension to standard system identification of detailed dynamics of a flexible wind turbine system

Baars, G.E. van; Mosterd, H.; Bongers, Peter

doi:10.1109/cdc.1993.325872

Cited by 5 publications

(4 citation statements)

References 4 publications

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“…If the output measurements are to a large extent corrupted with periodic signals of known frequencies, it is possible to construct virtual input signals with corresponding frequencies that are able to account for periodic components in the outputs [22]. The operation of such signals can be explained for the example of a wind turbine: the outputs are affected by periodic signals of unknown amplitude and phase, but which are directly correlated to the rotor azimuth ψ k and higher harmonics.…”

Section: Matricesmentioning

confidence: 99%

Closed-loop MOESP subspace model identification with parametrisable disturbances

Veen

Wingerden

Verhaegen

2010

49th IEEE Conference on Decision and Control (CDC)

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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.

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Section: Matricesmentioning

confidence: 99%

Closed-loop MOESP subspace model identification with parametrisable disturbances

Veen

Wingerden

Verhaegen

2010

49th IEEE Conference on Decision and Control (CDC)

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“…An LTI system identification is well established and a few applications can be reported in the wind energy [12][13][14][15]. However, the techniques used are all based on the open-loop setting and will give biased results in the closed-loop setting [29].…”

Section: Simulation Studymentioning

confidence: 99%

“…This implies that system identification gives a compact-sized model that is suitable for controller (re)design, load calculations, and model validation. Linear time-invariant (LTI) system identification is well established and few applications can be reported in the wind energy community [12][13][14][15]. However, wind turbines are nonlinear systems and as stated before they can be reformulated in the LPV framework.…”

Section: Introductionmentioning

confidence: 99%

Closed‐loop identification of the time‐varying dynamics of variable‐speed wind turbines

Wingerden

Houtzager

Felici

et al. 2008

Intl J Robust & Nonlinear

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SUMMARYThe trend with offshore wind turbines is to increase the rotor diameter as much as possible to decrease the costs per kWh. The increasing dimensions have led to the relative increase in the loads on the wind turbine structure. Because of the increasing rotor size and the spatial load variations along the blade, it is necessary to react to turbulence in a more detailed way: each blade separately and at several separate radial distances. This combined with the strong nonlinear behavior of wind turbines motivates the need for accurate linear parameter-varying (LPV) models for which advanced control synthesis techniques exist within the robust control framework. In this paper we present a closed-loop LPV identification algorithm that uses dedicated scheduling sequences to identify the rotational dynamics of a wind turbine. We assume that the system undergoes the same time variation several times, which makes it possible to use timeinvariant identification methods as the input and the output data are chosen from the same point in the variation of the system. We use time-invariant techniques to identify a number of extended observability matrices and state sequences that are inherent to subspace identification identified in a different state basis. We show that by formulating an intersection problem all states can be reconstructed in a general state basis from which the system matrices can be estimated. The novel algorithm is applied on a wind turbine model operating in closed loop.

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“…When the periodicity of the disturbances are known, e.g. with the identification techniques in van Baars et al and van Wingerden et al , it is even possible to relate the lifted covariance matrix

{\overset{R}{true}}_{n}

with the variance of the period time ph by a first‐order approximation as

{\overset{\overset{R}{true}}{true}}_{n} MathClass-rel= \frac{\partial {\overset{d}{true}}_{k MathClass-punc, p} ((), ph)}{∂ph} var ((), ph) \frac{\partial {\overset{d}{true}}_{k MathClass-punc, p}^{T} ((), ph)}{∂ph}

where the basis functions in

{\overset{d}{true}}_{k}

are used to express the periodic disturbances. Both approaches perform for small variations in period time; however, the latter approach is preferred in this case.…”

Section: Repetitive Control Designmentioning

confidence: 99%

Wind turbine load reduction by rejecting the periodic load disturbances

2012

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For the cost per kilowatt hour to be decreased, the trend in offshore wind turbines is to increase the rotor diameter as much as possible. The increasing dimensions have led to a relative increase of the loads on the wind turbine structure; thus, it is necessary to react to disturbances in a more detailed way, e.g. each blade separately. The disturbances acting on an individual wind turbine blade are to a large extent deterministic; for instance, tower shadow, wind shear, yawed error and gravity are depending on the rotational speed and azimuth angle and will change slowly over time. This paper aims to contribute to the development of individually pitch‐controlled blades by proposing a lifted repetitive controller that can reject these periodic load disturbances for modern fixed‐speed wind turbines and modern variable‐speed wind turbines operating above‐rated. The performance of the repetitive control method is evaluated on the UPWIND 5 MW wind turbine model and compared with typical individual pitch control. Simulation results indicate that for relatively slow changing periodic wind disturbances, this lifted repetitive control method can significantly reduce the vibrations in the wind turbine structure with considerably less high‐frequent control action. Copyright © 2012 John Wiley & Sons, Ltd.

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Extension to standard system identification of detailed dynamics of a flexible wind turbine system

Cited by 5 publications

References 4 publications

Closed-loop MOESP subspace model identification with parametrisable disturbances

Closed-loop MOESP subspace model identification with parametrisable disturbances

Closed‐loop identification of the time‐varying dynamics of variable‐speed wind turbines

Wind turbine load reduction by rejecting the periodic load disturbances

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