Wind Turbine Fatigue Loads Research Articles

Training requirements of a neural network used for fatigue load estimation of offshore wind turbines

To estimate fatigue loads of wind turbines via neural networks, costly load measurements are needed for training. Thus, our aim was to assess the minimum needed size of the training sample. We focused on the prediction of flapwise blade root bending moments with a neural network of eight inputs. Next to statistical testing of the training sample size, their representativeness compared to a one-year measurement as well as seasonal effects were investigated. Our results showed that training samples of about 2016 records of 10-minute statistics are representative and enable a reliable prediction independent from seasonal effects.

Fatigue Load Sensitivity-Based Optimal Active Power Dispatch For Wind Farms

This paper proposes an optimal active power dispatch algorithm for wind farms based on wind turbine (WT) load sensitivity. The control objectives include tracking power references from the system operator and minimizing fatigue loads experienced by WTs. The sensitivity of WT fatigue loads to power references is defined which simplifies the formulation of the optimal power dispatch problem. Since the sensitivity value is calculated at the local WT controller, the computation burden of the central wind farm controller is largely reduced. Moreover, explicit analytical equations of the fatigue load sensitivity are derived, which significantly improves the computation efficiency of the local WT controller. The proposed algorithm can be implemented in different active power control schemes. Case studies were conducted with a wind farm under balance control for both low and high wind conditions. By comparing the rainflow cycles and damage equivalent load (DEL), the efficacy of the proposed algorithm is verified.

Analysing wind turbine fatigue load prediction: The impact of wind farm flow conditions

Lifetime evaluation with fatigue loads is commonly used in the design phase of wind turbines, but rarely during operation due to the cost of extra measurements. Fatigue load prediction with neural networks, using existing SCADA signals, is a potential cost-effective alternative to continuously monitor lifetime consumption. However, although assessments for turbines in wind farm flow have been pointed out as deficient, the evaluations were limited to single cases and the implication for the design of a monitoring system was not discussed. Hence, we proposed metrics to evaluate prediction quality and, using one year of measurements at two wind turbines, we evaluated predictions in six different flow conditions. The quality of fatigue load predictions were evaluated for bending moments of two blades, in edgewise and flapwise directions. Results, based on 48 analyses, demonstrated that prediction quality varies marginally with varying flow conditions. Predictions were accurate in all cases and had an average error below 1.5%, but their precision slightly deteriorated in wake flow conditions. In general, results demonstrated that a reasonable monitoring system can be based on a neural network model without the need to distinguish between inflow conditions.

Innovative adaptive pitch control for small wind turbine fatigue load reduction

As a renewable source of energy, wind is widely used to produce electrical power. The progress of wind turbine technology can greatly benefit from the improvement of control algorithms. The pitch angle control of a horizontal axis wind turbine above the rated wind speed is a challenging issue related to the nonlinear aerodynamic behavior of blades. The linearization of aerodynamic model around nominal operating condition, as well as manufacturing deficiencies, result in unknown parameter uncertainties in a wind turbine model. Therefore, the performance of controller, which is designed based on the mathematical model, defects in practice. In the current paper, an adaptive self-tuning regulator (STR) configuration is proposed for the pitch control, so that the parameters of wind turbine model are constantly estimated and the controller gains are updated based on the assessed parameters. The STR structure consists of a recursive least square estimator and a proportional-integral-derivative (PID) controller with adjustable gains, which are determined by the pole placement method in a real-time routine. The robustness of the closed loop system is investigated by implementation of the control structure on an aero-servo-elastic wind turbine simulator. For the sake of comparison, a baseline gain scheduling PID controller, which is well-accepted for wind turbine pitch control, is designed. A comparison between the simulations of two controllers confirms a significant improvement in the closed-loop performance including less fluctuation of rotor speed and power besides minor fatigue loads on the blades and main-shaft.

Offshore wind turbine fatigue loads: The influence of alternative wave modeling for different turbulent and mean winds

The coupled hydro-aero-elastic response and fatigue loads of a bottom-supported offshore wind turbine under different wind conditions and for different wave modeling assumptions is the subject of this study. Nonlinear modeling of hydrodynamic forcing can bring about resonant vibrations of the tower leading to significant stress amplitude cycles. A comparison between linear and fully nonlinear wave models is presented, with consideration for different accompanying mean wind speeds and turbulence intensities. Hydrodynamic and aerodynamic loads acting on the support structure and on the rotor of a 5-MW wind turbine are modeled in a fully coupled hydro-aero-elastic solver. A key finding is that when the turbine is in a parked state, the widely used linear wave modeling approach significantly underestimates fatigue loads. On the other hand, when the wind turbine is in power production, aerodynamic loads are dominant and the effects due to consideration of nonlinear wave kinematics become less important.

小形風車翼の疲労荷重計算におけるIEC 61400-2 Ed.2 の簡略化した荷重モデルと空力弾性モデリングの比較

小形風車翼の疲労荷重計算におけるIEC 61400-2 Ed.2 の簡略化した荷重モデルと空力弾性モデリングの比較

Wind turbine fatigue loads as a function of atmospheric conditions offshore

In recent years, there has been a growing interest by the wind energy community to assess the impact of atmospheric stability on wind turbine performance; however, up to now, typically, stability is considered in several distinct arbitrary stability classes. As a consequence, each stability class considered still covers a wide range of conditions. In this paper, wind turbine fatigue loads are studied as a function of atmospheric stability without a classification system, and instead, atmospheric conditions are described by a continuous joint probability distribution of wind speed and stability. Simulated fatigue loads based upon this joint probability distribution have been compared with two distinct different cases, one in which seven stability classes are adopted and one neglecting atmospheric stability by following International Electrotechnical Commission (IEC) standards. It is found that for the offshore site considered in this study, fatigue loads of the blade root, rotor and tower loads significantly increase if one follows the IEC standards (by up to 28% for the tower loads) and decrease if one considers several stability classes (by up to 13% for the tower loads). The substantial decrease found for the specific stability classes can be limited by considering one stability class that coincides with the mean stability of a given hub height wind speed. The difference in simulated fatigue loads by adopting distinct stability classes is primarily caused by neglecting strong unstable conditions for which relatively high fatigue loads occur. Combined, it is found that one has to carefully consider all stability conditions in wind turbine fatigue load simulations. Copyright © 2016 John Wiley & Sons, Ltd.

Uncertainty in wind climate parameters and their influence on wind turbine fatigue loads

According to the wind turbine standard IEC 61400-1, structural integrity of wind turbines is determined either by direct reference to wind data or by load calculation. In both cases, deterministic values are applied and uncertainties neglected for the wind climate parameters and the structural resistance.The uncertainty related to the wind climate parameters depends highly on the presence, duration and quality of on-site wind measurements, and the perturbations introduced by flow modelling. For the wind speed distribution, the uncertainty is considered in assessment of the annual energy production. For other wind climate parameters which potentially have a large influence on the wind turbine loads, the uncertainty is often not well investigated.This paper presents a probabilistic framework for assessment of the structural reliability level of wind turbines in fatigue loading. Uncertainty of the site specific wind climate parameters at each turbine position is estimated based on the local wind measurements, speed-up factors and the distance between the wind turbine and the measuring position. The framework is demonstrated for a wind turbine project in flat terrain. The results show that the uncertainty in the site specific wind climate parameters normally accounts for 10–30% of the total uncertainty in the structural reliability analyses.

Dynamical measurement system for wind turbine fatigue load

A measurement system specially used in wind turbine fatigue load assessment is developed based on Labview platform and Control Area Network (CAN). By applying CAN bus communication technology, the system can perform data automatic acquisition, data stable transmission and data real-time monitoring. By adopting the technology of virtual instrument modular design, the system is designed to analyze the wind turbine mechanical load levels against wind and power, equivalent loads and lifetime fatigue loads, etc. Considering the effects of small load strengthening, low amplitude load damaging and multilevel load interaction, a novel fatigue lifetime prediction model is proposed to obtain more accurate and reliable prediction of blade fatigue life. With the developed measurement system, the in-field load measurements are performed and the results showed the system has satisfactory accuracy and good adaption, convenient operation, high integration, low cost and great practicality to load measurement of large wind turbine. And based on the proposed model the fatigue life of WT blade can be estimated more trustworthily and reliably.

Evaluation of wind farm effects on fatigue loads of an individual wind turbine at the EnBW Baltic 1 offshore wind farm

Turbulence in wake has special interest due to its strong connection with increment of fatigue loads. The aim of this paper is to evaluate the wind farm effects on fatigue loads of an individual wind turbine at the EnBW Baltic 1 offshore wind farm and compare the results with the statements suggested by IEC 61400-1 ed. 3 [1].From measurements, the study provides strong evidence that considerable wake effects up to 15 rotor diameters (D) downstream are related to the increase of fatigue loads in the analyzed turbine. The influence of the behavior of the upstream wind turbine's thrust coefficient (CT) can be observed in the analyzed curves for turbulence intensity and damage equivalent loads (DELs) in blade root flapwise and edgewise direction.

Research the Influencing Factors of the Low Wind Speed Wind Turbine Fatigue Loads

This paper analyzes three main factors (turbulence intensity, air density, annual average wind speed ) that influence the low wind speed wind turbine fatigue loads, In order to analyze the influence of each main parameters how to affect the fatigue load of low wind speed wind turbine, using a 2000kW wind turbine as an example on the simulation test , 3 turbulence, 4 air density and 7 annual average wind speed were employed. The results show that, with the air density, turbulence intensity and the annual average wind speed increases, the wind turbine of fatigue load increase in rule approximately. Based on the above rule, it can reduce fatigue loads and prolong the life of wind turbine in design optimization of low wind speed wind turbine and sit choice.

Research of the Analysis Method on the Three Basics of the Wind Turbine Fatigue Loads

The research has identified turbulence intensity, annual wind speed and air density as the three basics of fatigue loads, in this paper, we call it three basics for short. This paper presents a method to analyze the three basics of the wind turbine fatigue loads. It explains the fatigue loads analysis idea and method of the three basics and it use the analysis method to research the extent of the influence by using a 1650kW wind turbine as an example. It can be seen from the results that the wind resources increase one classification, the influence of the turbulence intensity is the greatest, then the annual wind speed, finally the air density.

Definition of the equivalent atmospheric stability for wind turbine fatigue load assessment

In this paper the dependence of wind turbine fatigue loads on atmospheric stability is assessed. It is shown that fatigue loads depend strongly on stability, and highest loads occur for very unstable conditions. For a given hub height wind speed one can define an equivalent atmospheric stability that corresponds to the same cumulative loads as if one performs an infinite amount of simulations for all stability conditions that may occur. It is shown that stability, conditionalised to hub height wind speed, is approximately normally distributed and the equivalent stability corresponds well to the mean stability for a given hub height wind speed. If one follows the IEC guidelines for offshore sites, neglecting atmospheric stability, one will compute higher cumulative lifetime fatigue loads (≈ 10%). This overestimation is caused by conservatism in both wind shear and turbulence levels, which is explicitly shown for the turbulence levels analyzed in this paper.

Combined wind turbine fatigue and ultimate load reduction by individual blade control

If each blade of the wind turbine has individual pitch actuator, there is possibility of employing the pitch system to mitigate structural loads through advanced control methods. Previously, considerable reduction of blade lifetime equivalent fatigue loads has been achieved by Individual Blade Control (IBC) and in addition, it has also been shown the potential in blade ultimate loads reduction. However, both fatigue and ultimate loads impact on the design and life of wind turbine blades. In this paper, the design and application of IBC that concurrently reduce both blade fatigue and ultimate loads is investigated. The contributions of blade load spectral components, which are 1P, 2P and edgewise mode from blade in-plane and/or out-of-plane bending moments, are firstly explored. Four different control options for reducing various combinations of these load components are compared. In response to the different spectral peaks of both fatigue and ultimate loads, the controller has been designed so that it can act on different frequency components which vary with wind speed. The performance of the IBC controller on fatigue and ultimate load reduction is assessed by simulating a 5MW exemplar wind turbine. Simulation results show that with a proper selection of controlling inputs at different wind speed, the use of a single combined IBC can achieve satisfactory reduction on both fatigue and ultimate loads.

Individual Pitch Control for Load Reduction Based on Norm Theory

As the capacity of wind turbine increases, unsteady blade loads and performance caused by asymmetrical effects like turbulence, wind shear and tower shadow lead to fatigue loads which seriously affect wind turbine life cycle. This paper focused on wind turbine fatigue load response characteristics, built the multiple input multiple output linearized matrix model, introduced individual pitch control algorithm for optimized disturbance control based on norm theory. Modeling, simulation and verification of the control algorithm are conducted in Matlab. The investigation is conducted based on a 2MW doubly-fed wind turbine. By comparing the results of wind turbine deflection rate and angle deflection rate to collective pitch control method, it shows the individual pitch control algorithm can significantly reduce wind turbine fatigue load, and the control effect is superior to traditional control algorithm.

A Review of the Effects of Ice Accretion on the Structural Behavior of Wind Turbines

Icing of wind turbines happens occasionally at different latitudes and locations in the world and consequently affects the wind turbine fatigue loads. Large ice accretion may cause wind turbine vibration due to uneven ice shedding, which could lead to structural failures in addition to hazardous issues accompanied with ice being shed off wind turbine blades. In this paper, a review study of the effects of ice accretion on the structural behavior of the wind turbines is presented.

S0503-5-4 風車疲労荷重に与える複雑地形風特性の影響([S0503-5]自然の流体エネルギー利用技術(5))

This paper shows results of aero-elastic on wind turbine fatigue load to clarify the effects of turbulence characteristics in complex terrain. The effects of turbulence intensity, longitudinal, lateral and normal component of turbulence standard deviation of wind speed fluctuations on the blade bending moment are compared. The results showed that the correction model of turbulence intensity for complex terrain described in the IEC 61400-1 is very conservative for normal operation mode.

Wind turbines: New challenges and advanced control solutions

Wind turbines: New challenges and advanced control solutions

Feedback–feedforward individual pitch control for wind turbine load reduction

AbstractThis paper focuses on the problem of wind turbine fatigue load reduction by means of individual pitch control (IPC). The control approach has a two‐degree‐of‐freedom structure, consisting of an optimal multivariable LQG controller and a feedforward disturbance rejection controller based on estimated wind speed signals. To make the control design problem time invariant, all signals are transformed to the non‐rotating reference frame using the Coleman transformation. In the Coleman domain, the LQG control objective is minimization of the rotor tilt and yaw moments, whereas the feedforward controller tries to achieve even further improvement by rejecting the influence of the low‐frequency components of the wind on the rotor moments. To this end, the tilt‐ and yaw‐oriented components of the blade‐effective wind speeds are approximated using stochastic random walk models, the states of which are then augmented with the turbine states and estimated using a Kalman filter. The effects of these (estimated) disturbances on the controlled outputs are then reduced using stable dynamic model inversion. The approach is tested and compared with the conventional IPC method in simulation studies with models of different complexities. The results demonstrate very good load reduction at not only low frequencies (1p blade fatigue load reduction) but also at the 3p frequency, giving rise to fatigue load reduction of the non‐rotating turbine components. Copyright © 2008 John Wiley & Sons, Ltd.

A comparison of fatigue loads of wind turbine resulting from a non-Gaussian turbulence model vs. standard ones

This project funded by the federal ministry of education and research from the research group 'Wind turbulence and its significance in the use of wind energy' handles a comparison between the load ranges for horizontal axis wind turbines resulting from different turbulence models, i.e. between the usual models as defined in the standards and a new model designed by Friedrich and Kleinhans. This should enable an evaluation of the relevance of this new model for wind modelling for wind turbines and if so, provide the community with new tools in wind simulation. Indeed, spectral models do not well reproduce extreme wind increments as met in gusts. Those models simulate using purely Gaussian statistics. However, measurements show that those increments do not follow normal statistics. The new model developed aims at correcting this problem. The turbulence models used are the Kaimal, von Karman and Mann models as defined in the IEC guidelines and the Friedrich-Kleinhans model, based on stochastic processes called Continuous Time Random Walks. The comparison is based on load ranges resulting from an RFC analysis of 100 time series obtained for 100 different seed numbers. Five wind speeds are investigated. The aeroelastic code used is FLEX5. The main conclusion that can be drawn from this study is that the non-Gaussian Friedrich-Kleinhans model produces loads that are significantly different from the loads obtained with the Kaimal model. That proves that the form of the tails of the increment distribution has a major influence on the loads of the wind turbine and should be considered when making fatigue calculations.