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Preview: Wind Energy

Wind Energy

Wiley Online Library : Wind Energy

Published: 2017-10-01T00:00:00-05:00


Teeter design for lowest extreme loads during end impacts


Two bladed wind turbines are discussed as a possible turbine alternative for offshore use as they show a potential to save cost of energy. But compared to three-bladed turbines, their dynamic behavior is much more challenging. A possible solution to handle these larger dynamic loads is the use of a teeter hinge, which can significantly reduce fatigue loads. In contrast to that, extreme loads, coming from teeter end impacts, are often described as a problem for teetered turbines. There are different design parameters of the teeter system of a turbine, which have an influence on extreme loads during teeter end impacts. Despite numerous studies on teeter movement and load reduction potentials of operational loads, scientific literature does not give information about suitable load-reducing combinations of teeter design parameters and their influence on extreme loads. This paper, which is a summary of a PhD thesis, analyses which combination of teeter parameters has the largest load-reducing influence on extreme loads. Aeroelastic load simulations of the teetered turbine CART2 from the NREL test site and one of today's commercial two-bladed turbines, the SCD3MW from aerodyn (both pitch controlled upwind turbines), will be used.

Individual pitch control for 2-bladed wind turbines via multiblade multilag transformation


Two-bladed wind turbines have regained the attention of the community thanks to the advantages in manufacturing cost provided by the lower number of blades and the ease of implementation of effective passive systems for load reduction (ie, teetering pin). Considering both teetering and nonteetering architectures, the dynamics of 2-bladed turbines is different from that of 3-bladed machines especially in terms of how multiples of the rotor frequencies in blade signals are translated on the fixed system. Such characteristics have hampered the adoption of active control laws for load mitigation based on individual pitch control, extensively studied for 3-bladed turbines. A basic element for control development allowing to capture the essence of the relationship between signals on the blades and the fixed system on 2-bladed turbines–represented by the Coleman transformation for 3-bladed turbines–has not been identified yet. The present paper tries to fill the gap, presenting an extended transformation–called multiblade multilag–applicable to turbines with an arbitrary number of blades, providing a systematic way to link rotor signals to fixed system signals, thus allowing the application of control algorithms for individual pitch control developed for 3-bladed turbines to the 2-bladed case. The paper addresses the problem first at a theoretical level, and subsequently providing applicative results from simulations on virtual models of teetering and nonteetering 2-bladed turbines. The proposed transformation algorithm and control laws allow to effectively reduce some relevant loads and motions respectively in the nonteetering and teetering scenarios, through a cyclic pitch input.

Statistical learning for wind power: A modeling and stability study towards forecasting


We focus on wind power modeling using machine learning techniques. We show on real data provided by the wind energy company Maïa Eolis that parametric models even following closely the physical equation relating wind production to wind speed are outperformed by intelligent learning algorithms. In particular, the CART-Bagging algorithm gives very stable and promising results. Besides, as a step towards forecast, we quantify the impact of using deteriorated wind measures on the performances. We show also on this application that the default methodology to select a subset of predictors provided in the standard random forest package can be refined, especially when there exists among the predictors one variable, which has a major impact.

Analysis of reactive power strategies in HVDC-connected wind power plant clusters


Offshore wind power plants (WPPs) built near each other but far from shore usually connect to the main grid by a common high-voltage DC (HVDC) transmission system. In the resulting decoupled offshore grid, the wind turbine converters and the high-voltage DC voltage-source converter share the ability to inject or absorb reactive power. The overall reactive power control dispatch influences the power flows in the grid and hence the associated power losses. This paper evaluates the respective power losses in HVDC-connected WPP clusters when applying 5 different reactive power control strategies. The case study is made for a 1.2-GW–rated cluster comprising 3 WPP and is implemented in a combined load flow and converter loss model. A large set of feasible operating points for the system is analyzed for each strategy. The results show that a selection of simulations with equal wind speeds is sufficient for the annual energy production comparison. It is found that the continuous operation of the WPPs with unity power factor has a superior performance with low communication requirements compared with the other conventional strategies. The optimization-based strategy, which is developed in this article, allows a further reduction of losses mainly because of the higher offshore grid voltage level imposed by the high-voltage DC voltage-source converter. Reactive power control in HVDC-connected WPP clusters change significantly the overall power losses of the system, which depend rather on the total sum of the injected active power than on the variance of wind speeds inside the cluster.

Tailoring incoming shear and turbulence profiles for lab-scale wind turbines


An active grid is used to generate a variety of turbulent shear profiles in a wind tunnel. The vertical bars are set to flap through varying angles across the test section producing a variation in the perceived solidity, resulting in a mean shear. The horizontal bars are used in a fully random operational mode to set the background turbulence level. It is demonstrated that mean velocity profiles with approximately the same shear can be produced with different turbulence intensities and local turbulent Reynolds numbers based on the Taylor microscale, λ. Conversely, it is also demonstrated that flows can be produced with similar turbulence intensity profiles but different mean shear. It is confirmed that the length scales and dynamics, the latter being assessed through the velocity spectra and probability density functions, do not vary significantly across the investigation domain. Such flows are of particular relevance for studies investigating the effect of in-flow conditions on obstacles where these studies wish to decouple the effects of turbulence intensity and mean shear, a feat previously unattainable in experimental facilities. Given that the power output of wind turbines is known to be a function of both mean shear and turbulence intensity, the experimental methodology presented herein is invaluable to the wind turbine model testing community who, at present, cannot exert such control authority over the in-flow conditions.

A simple model of the wind turbine induction zone derived from numerical simulations


The induction zone in front of different wind turbine rotors is studied by means of steady-state Navier-Stokes simulations combined with an actuator disk approach. It is shown that, for distances beyond 1 rotor radius upstream of the rotors, the induced velocity is self-similar and independent of the rotor geometry. On the basis of these findings, a simple analytical model of the induction zone of wind turbines is proposed.

Measurement of mechanical loads in large wind turbines: Problems on calibration of strain gage bridges and analysis of uncertainty


The paper discusses the complexity of calibration of strain gage full bridges applied to measure mechanical loads in large wind turbines, when direct application of calibration loads is not feasible. In particular, at first, it presents a generalized static-dynamic mechanical model which allows to calibrate the strain gage full bridges using its own unbalanced masses to generate known reference inputs. Then, the paper discusses the uncertainty associated to such a calibration, according to the ISO/IEC Guide 98-3:2008 “Guide to the Expression of Uncertainty in Measurement”. The uncertainty of the reference input and the following calibration is discussed, which is often larger than the target set by the standard IEC-61400-13 used for wind turbine type certification. The paper comments on the attainable range of calibration which is rather limited with respect to expected load range in operation. Even if calibration should take place in isothermal effects, this is not always the case in real world practice. Therefore, the thermal effects on strain gage bridges are also discussed, putting into evidence its influence on calibration uncertainty both for full bridges in T configuration and in parallel configuration.

Aeroelastic multidisciplinary design optimization of a swept wind turbine blade


Mitigating loads on a wind turbine rotor can reduce the cost of energy. Sweeping blades produces a structural coupling between flapwise bending and torsion, which can be used for load alleviation purposes. A multidisciplinary design optimization (MDO) problem is formulated including the blade sweep as a design variable. A multifidelity approach is used to confront the crucial effects of structural coupling on the estimation of the loads. During the MDO, ultimate and damage equivalent loads are estimated using steady-state and frequency-domain–based models, respectively. The final designs are verified against time-domain full design load basis aeroelastic simulations to ensure that they comply with the constraints. A 10-MW wind turbine blade is optimized by minimizing a cost function that includes mass and blade root flapwise fatigue loading. The design space is subjected to constraints that represent all the necessary requirements for standard design of wind turbines. Simultaneous aerodynamic and structural optimization is performed with and without sweep as a design variable. When sweep is included in the MDO process, further minimization of the cost function can be obtained. To show this achievement, a set of optimized straight blade designs is compared to a set of optimized swept blade designs. Relative to the respective optimized straight designs, the blade mass of the swept blades is reduced of an extra 2% to 3% and the blade root flapwise fatigue damage equivalent load by a further 8%.

Bird detection and species classification with time-lapse images around a wind farm: Dataset construction and evaluation


Collisions of birds, especially endangered species, with wind turbines is a major environmental concern. Automatic bird monitoring can be of aid in resolving the issue, particularly in environmental risk assessments and real-time collision avoidance. For automatic recognition of birds in images, a clean, detailed, and realistic dataset to learn features and classifiers is crucial for any machine-learning-based method. Here, we constructed a bird image dataset that is derived from the actual environment of a wind farm and that is useful for examining realistic challenges in bird recognition in practice. It consists of high-resolution images covering a wide monitoring area around a turbine. The birds captured in these images are at relatively low resolution and are hierarchically labeled by experts for fine-grained species classification. We conducted evaluations of state-of-the-art image recognition methods by using this dataset. The evaluations revealed that a deep-learning-based method and a simpler traditional learning method were almost equally successful at detection, while the former captures more generalized features. The most promising results were provided by the deep-learning-based method in classification. The best methods in our experiments recorded a 0.98 true positive rate for bird detection at a false positive rate of 0.05 and a 0.85 true positive rate for species classification at a false positive rate of 0.1.

Wind turbine performance decline in Sweden


We show that Swedish wind turbines constructed before 2007 lose 0.15 capacity factor percentage points per year, corresponding to a lifetime energy loss of 6%. A gradual increase of downtime accounts for around one third of the deterioration and worsened efficiency for the remaining. Although the performance loss in Sweden is considerably smaller than previously reported in the UK, it is statistically significant and calls for a revision of the industry practice for wind energy calculations. The study is based on two partly overlapping datasets, comprising 1,100 monthly and 1,300 hourly time series spanning 5–25 years each.

Effect of tower and nacelle on the flow past a wind turbine


Large eddy simulations (LES) of the flow past a wind turbine with and without tower and nacelle have been performed at 2 tip speed ratios (TSR, λ=ωR/U∞), λ=3 and 6, where the latter corresponds to design conditions. The turbine model is placed in a virtual wind tunnel to reproduce the “Blind test 1” experiment performed at the Norwegian University of Science and Technology (NTNU) closed-loop wind tunnel. The wind turbine was modeled using the actuator line model for the rotor blades and the immersed boundary method for the tower and nacelle. The aim of the paper is to highlight the impact of tower and nacelle on the turbine wake. Therefore, a second set of simulations with the rotating blades only (neglecting the tower and nacelle) has been performed as reference. Present results are compared with the experimental measurements made at NTNU and numerical simulations available in the literature. The tower and nacelle not only produce a velocity deficit in the wake but they also affect the turbulent kinetic energy and the fluxes. The wake of the tower interacts with that generated by the turbine blades promoting the breakdown of the tip vortex and increasing the mean kinetic energy flux into the wake. When tower and nacelle are modeled in the numerical simulations, results improve significantly both in the near wake and in the far wake.

Generating short-term probabilistic wind power scenarios via nonparametric forecast error density estimators


Forecasts of available wind power are critical in key electric power systems operations planning problems, including economic dispatch and unit commitment. Such forecasts are necessarily uncertain, limiting the reliability and cost-effectiveness of operations planning models based on a single deterministic or “point” forecast. A common approach to address this limitation involves the use of a number of probabilistic scenarios, each specifying a possible trajectory of wind power production, with associated probability. We present and analyze a novel method for generating probabilistic wind power scenarios, leveraging available historical information in the form of forecasted and corresponding observed wind power time series. We estimate nonparametric forecast error densities, specifically using epi-spline basis functions, allowing us to capture the skewed and nonparametric nature of error densities observed in real-world data. We then describe a method to generate probabilistic scenarios from these basis functions that allows users to control for the degree to which extreme errors are captured. We compare the performance of our approach to the current state-of-the-art considering publicly available data associated with the Bonneville Power Administration, analyzing aggregate production of a number of wind farms over a large geographic region. Finally, we discuss the advantages of our approach in the context of specific power systems operations planning problems: stochastic unit commitment and economic dispatch. Our methodology is embodied in the joint Sandia–University of California Davis Prescient software package for assessing and analyzing stochastic operations strategies.

The effect of timescales on wind farm power variability with nonlinear model predictive control


Model predictive control techniques enable operators to balance multiple objectives in large wind farms, but the controller design depends on modeling effects that propagate at different timescales. This paper uses nonlinear model predictive control to investigate how wind farm power variability can be reduced both by varying ratios of three timescales impacting the system control and by inclusion of a power variability minimization measure in the controller objective function. Tests were conducted to assess how different timescale ratios affect the average farm power and power variability. Power variability measures are shown to be sensitive to the ratio of the incident wind period and the turbine time delay, particularly for cases with dominant incident wind frequencies. The average farm power increases in a series of steps as the controller time horizon increases, which corresponds to time horizon values required for wakes disturbances to propagate to downstream turbines. A second set of tests was conducted in which various measures of power variability were incorporated into the controller objective function and shown to yield significant reductions in farm power variability without significant reductions in farm power output. The controller was found to utilize two different approaches for achieving power variability reduction depending on the formulation of the controller objective function. These results have important implications for the design and operation of wind power plants, including the importance of considering the frequency components of wind during turbine siting and the potential to reduce power variability through the use of farm-level coordinated control. Copyright © 2017 John Wiley & Sons, Ltd.

Hybrid vortex simulations of wind turbines using a three-dimensional viscous–inviscid panel method


A hybrid filament-mesh vortex method is proposed and validated to predict the aerodynamic performance of wind turbine rotors and to simulate the resulting wake. Its novelty consists of using a hybrid method to accurately simulate the wake downstream of the wind turbine while reducing the computational time used by the method. The proposed method uses a hybrid approach, where the near wake is resolved by using vortex filaments, which carry the vorticity shed by the trailing edge of the blades. The interaction of the vortex filaments in the near vicinity of the wind turbine is evaluated using a direct calculation, whereas the contribution from the large downstream wake is calculated using a mesh-based method. The hybrid method is first validated in detail against the well-known MEXICO experiment, using the direct filament method as a comparison. The second part of the validation includes a study of the influence of the time-integration scheme used for evolving the wake in time, aeroelastic simulations of the National Renewable Energy Laboratory 5 MW wind turbine and an analysis of the central processing unit time showing the gains of using the hybrid filament-mesh method. Copyright © 2017 John Wiley & Sons, Ltd.

Quantification of power losses due to wind turbine wake interactions through SCADA, meteorological and wind LiDAR data


Power production of an onshore wind farm is investigated through supervisory control and data acquisition data, while the wind field is monitored through scanning light detection and ranging measurements and meteorological data acquired from a met-tower located in proximity to the turbine array. The power production of each turbine is analysed as functions of the operating region of the power curve, wind direction and atmospheric stability. Five different methods are used to estimate the potential wind power as a function of time, enabling an estimation of power losses connected with wake interactions. The most robust method from a statistical standpoint is that based on the evaluation of a reference wind velocity at hub height and experimental mean power curves calculated for each turbine and different atmospheric stability regimes. The synergistic analysis of these various datasets shows that power losses are significant for wind velocities higher than cut-in wind speed and lower than rated wind speed of the turbines. Furthermore, power losses are larger under stable atmospheric conditions than for convective regimes, which is a consequence of the stability-driven variability in wake evolution. Light detection and ranging measurements confirm that wind turbine wakes recover faster under convective regimes, thus alleviating detrimental effects due to wake interactions. For the wind farm under examination, power loss due to wake shadowing effects is estimated to be about 4% and 2% of the total power production when operating under stable and convective conditions, respectively. However, cases with power losses about 60-80% of the potential power are systematically observed for specific wind turbines and wind directions. Copyright © 2017 John Wiley & Sons, Ltd.

Realistic simulations of the July 1, 2011 severe wind event over the Buffalo Ridge Wind Farm


Severe winds from thunderstorm outflows pose a challenge to wind turbine arrays. They can cause significant power ramps and disruption in energy production. They can also cause extreme structural damage to turbines as was seen in the severe storm event over the Buffalo Ridge Wind Farm on July 1, 2011. At this southwestern Minnesota site, blades from multiple turbines broke away and a tower buckled in the intense winds. In this study, we attempt to characterize meteorological conditions over the Buffalo Ridge Wind Farm area during this event. The observational network included NEXRAD radars, automated surface observation stations and a wind profiler. Storm reports from the Storm Prediction Center and damage surveys provided additional insight to the in situ measurements. Even with these datasets, assessing wind speeds around turbine rotors is difficult. Thus, Weather Research and Forecasting model simulations of the event are carried out that consider current and anticipated future operational model setups. This work addresses model spatial resolution versus parameterization complexity. Parameterizations of the planetary boundary layer and microphysics processes are evaluated based on their impact on storm dynamics and the low-level wind field. Results are also compared with the Wind Integration National Dataset, which utilizes data assimilation and an extensive continental domain. Enhanced horizontal resolution with simplistic parameterization helps increase resolved wind speeds and ramp intensity. Enhanced sophistication of microphysics parameterizations also helps increase resolved wind speeds, improve storm timing and structure and resolve higher values of turbulent kinetic energy in the lowest 1 km of the atmosphere. Copyright © 2017 John Wiley & Sons, Ltd.

Optimal offering and allocation policies for wind power in energy and reserve markets


Proliferation of wind power generation is increasingly making this power source an important asset in designs of energy and reserve markets. Intuitively, wind power producers will require the development of new offering strategies that maximize the expected profit in both energy and reserve markets while fulfilling the market rules and its operational limits. In this paper, we implement and exploit the controllability of the proportional control strategy. This strategy allows the splitting of potentially available wind power generation in energy and reserve markets. In addition, we take advantage of better forecast information from the different day-ahead and balancing stages, allowing different shares of energy and reserve in both stages. Under these assumptions, different mathematical methods able to deal with the uncertain nature of wind power generation, namely, stochastic programming, with McCormick relaxation and piecewise linear decision rules are adapted and tested aiming to maximize the expected revenue for participating in both energy and reserve markets, while accounting for estimated balancing costs for failing to provide energy and reserve. A set of numerical examples, as well as a case study based on real data, allow the analysis and evaluation of the performance and behavior of such techniques. An important conclusion is that the use of the proposed approaches offers a degree of freedom in terms of minimizing balancing costs for the wind power producer strategically to participate in both energy and reserve markets. Copyright © 2017 John Wiley & Sons, Ltd.

Assessing the seismic wavefield of a wind turbine using polarization analysis


Ambient seismic noise can often be seen as problematic but with the right analysis can act as a tool to image the Earth. Wind turbines are known to generate low frequency vibrations; however, the wave types that are generated are currently unknown. Characterizing these vibrations will allow wind turbines to be used as a seismic source and be of value to geotechnical applications and seismic interferometry. This paper uses polarization analysis of the seismic wavefield around a small wind turbine to identify the type of wave being generated by the turbine and to clarify the source. The seismic data recorded 190 m from the wind turbine are processed using a window length of 0.1 s and bandpass filtered on a selection of frequency ranges. Polarization analysis is performed for two different wind speed ranges, in order to show the variation of wave characteristics between operational and non-operational modes of the wind turbine. Polarized surface waves are identified as the predominant wave type at blade rotation harmonics, making this work particularly relevant to multichannel analysis of surface waves and seismic interferometry. Copyright © 2017 John Wiley & Sons, Ltd.

Cover Image


The cover image, by Jun-Tae Seong et al., is based on the Research Article Centrifuge modeling to evaluate natural frequency and seismic behavior of offshore wind turbine considering SFSI, DOI 10.1002/we.2127.

Issue Information


No abstract is available for this article.

Development of a modified stochastic subspace identification method for rapid structural assessment of in-service utility-scale wind turbine towers


The strong drive to harness wind energy has recently led to rapid growth of wind farm construction. Wind turbine towers with increased sizes and flexibility experience large vibrations. Structural health monitoring of wind turbines is proposed in the wind energy industry to ensure their proper performance and save maintenance costs. This study proposes a system identification method for vibration-based structural assessment of wind turbine towers. This method developed based on the stochastic subspace identification method can identify modal parameters of structures in operating conditions with harmonic components in excitations. It benefits wind turbine tower structural health assessment because classical operational modal analysis methods can fail as periodic rotation excitation from a turbine introduces harmonic disturbance to tower structure response data. The effectiveness, accuracy and robustness of the proposed method were numerically investigated and verified through a lumped-mass system model. The method was then applied to an in-service utility-scale wind turbine tower. The field testing campaign and modal parameter identification as well as structural assessment results were presented. Copyright © 2017 John Wiley & Sons, Ltd.

Performance evaluation of a floating lidar buoy in nearshore conditions


This work provides a signal-processing and statistical-error analysis methodology to assess key performance indicators for a floating Doppler wind lidar. The study introduces the raw-to-clean data processing chain, error assessment indicators and key performance indicators, as well as two filtering methods at post-processing level to alleviate the impact of angular motion and spatial variability of the wind flow on the performance indicators. Towards this aim, the study mainly revisits horizontal wind speed (HWS) and turbulence intensity measurements with a floating ZephIR 300 lidar buoy during a 38 day nearshore test campaign in Pont del Petroli (Barcelona). Typical day cases along with overall statistics for the whole campaign are discussed to illustrate the methodology and processing tools developed. Copyright © 2017 John Wiley & Sons, Ltd.

Aerofoil trailing-edge noise prediction models for wind turbine applications


This paper proposes a modified TNO model for the prediction of aerofoil trailing-edge noise for wind turbine applications. The capabilities of the current modified model and four variants of the TNO model are analysed through a comprehensive study which includes 10 aerofoils and involves two different wind tunnels. The Reynolds numbers considered are between 1.13 and 3.41 million, and the effective angles of attack are between −2.20° and 13.58°. The merit of a model is assessed by comparing two aspects of the numerically predicted and the experimentally measured sound pressure level spectra: the sound pressure level difference between two different aerofoils at similar lift coefficients within a certain frequency range (referred to as the delta noise); and the closeness in terms of spectral magnitude and shape of the predicted and measured sound pressure level spectra. The current modified model is developed by deriving new formulations for the computation of the wall pressure fluctuation spectrum. This is achieved by using the approximate ratio of the normal Reynolds stress components for an anisotropic flow over a flat plate to estimate the vertical Reynolds stress component, and by introducing new stretching factors to take the effects of turbulent flow anisotropy into account. Compared with the four TNO model variants tested, the current modified model has strong delta noise prediction ability, and is able to predict sound pressure level spectra that are more consistent and closer to measurements for the vast majority of aerofoils and flow conditions tested in the two wind tunnels. Copyright © 2017 John Wiley & Sons, Ltd.

Wind tunnel investigation on the effect of the turbine tower on wind turbines wake symmetry


In wind farms, the wake of the upstream turbines becomes the inflow for the downstream machines. Ideally, the turbine wake is a stable vortex system. In reality, because of factors like background turbulence, mean flow shear, and tower-wake interaction, the wake velocity deficit is not symmetric and is displaced away from its mean position. The irregular velocity profile leads to a decreased efficiency and increased blade stress levels for the downstream turbines. The object of this work is the experimental investigation of the effect of the wind turbine tower on the symmetry and displacement of the wake velocity deficit induced by one and two in-line model wind turbines (,D= 0.9 m). The results of the experiments, performed in the closed-loop wind tunnel of the Norwegian University of Science and Technology in Trondheim (Norway), showed that the wake of the single turbine expanded more in the horizontal direction (side-wall normal) than in the vertical (floor normal) direction and that the center of the wake vortex had a tendency to move toward the wind tunnel floor as it was advected downstream from the rotor. The wake of the turbine tandem showed a similar behavior, with a larger degree of non-symmetry. The analysis of the cross-stream velocity profiles revealed that the non-symmetries were caused by a different cross-stream momentum transport in the top-tip and bottom-tip region, induced by the turbine tower wake. In fact, when a second additional turbine tower, mirroring the original one, was installed above the turbine nacelle, the wake recovered its symmetric structure. Copyright © 2017 John Wiley & Sons, Ltd.

Load reduction on a clipper liberty wind turbine with linear parameter-varying individual blade pitch control


The increasing size of modern wind turbines also increases the structural loads caused by effects such as turbulence or asymmetries in the inflowing wind field. Consequently, the use of advanced control algorithms for active load reduction has become a relevant part of current wind turbine control systems. In this paper, an individual blade pitch control law is designed using multivariable linear parameter-varying control techniques. It reduces the structural loads both on the rotating and non-rotating parts of the turbine. Classical individual blade pitch control strategies rely on single-control loops with low bandwidth. The proposed approach makes it possible to use a higher bandwidth since it accounts for coupling at higher frequencies. A controller is designed for the utility-scale 2.5 MW Liberty research turbine operated by the University of Minnesota. Stability and performance are verified using the high-fidelity nonlinear simulation and baseline controllers that were directly obtained from the manufacturer. Copyright © 2017 John Wiley & Sons, Ltd.

Centrifuge modeling to evaluate natural frequency and seismic behavior of offshore wind turbine considering SFSI


Understanding of dynamic response of offshore wind turbine is important to reduce vibration of offshore wind turbine induced by structural and environmental loadings. Although dynamic characteristics of the offshore wind turbine such as natural frequency and seismic behavior are affected by foundation and soil conditions, there are little experimental studies about the dynamic behavior of offshore wind turbine with consideration of proper soil–foundation–structure interaction (SFSI). The goal of this research is to evaluate the natural frequency and seismic behavior of offshore wind turbine with a monopod foundation considering SFSI. Scaled model of offshore wind turbine and monopod foundation is produced for this research. Geotechnical centrifuge tests in fixed-based and SFSI condition were performed to measure natural frequency in each case. Also, a series of seismic loadings with different intensities are applied to observe seismic behaviors of the offshore wind turbine during the earthquake and permanent changes after the earthquake. Experimental results show apparent natural frequency reduction in SFSI condition compared with the fixed-based condition, non-linear changes in dynamic response during a series of earthquakes and permanent changes occurred in natural frequency and rotational displacement after earthquakes. Copyright © 2017 John Wiley & Sons, Ltd.