Empirical Wind Turbine Load Distributions Using Field Data

2008 ◽  
Vol 130 (1) ◽  
Author(s):  
Puneet Agarwal ◽  
Lance Manuel
Keyword(s):  
Wind Speed ◽  
Wind Turbine ◽  
Field Data ◽  
Offshore Wind ◽  
Full Time ◽  
Return Periods ◽  
Load Distributions ◽  
Design Loads ◽  
Summary Data

In the design of land-based or offshore wind turbines for ultimate limit states, long-term loads associated with return periods on the order of the service life (20years, usually) must be estimated. This requires statistical extrapolation from turbine load data that may be obtained by simulation or by field tests. The present study illustrates such extrapolation that uses field data from the Blyth offshore wind farm in the United Kingdom, where a 2MW wind turbine was instrumented, and environment and load data were recorded. From this measurement campaign, the load data available are in two different formats: as 10min statistics (referred to as “summary” data) or as full time series (referred to as “campaign” data). The characteristics of the site and environment and, hence, that of the turbine response are strikingly different for winds from the sea and winds from the shore. The load data (here, only the mudline bending moment is studied) at the Blyth site are hence separated depending on wind regime. By integrating load distributions conditional on the environment with the relative likelihood of the different environmental conditions, long-term loads associated with specified return periods can be derived. This is achieved here using the peak-over-threshold method based on campaign data but long-term loads are compared with similar estimates based on the summary data. Winds from the shore are seen to govern the long-term loads at the site. Though the influence of wave heights on turbine long-term loads is smaller than that of wind speed, there is possible resonance of tower dynamics induced by the waves; still, to first order, it is largely the wind speed and turbulence intensity that control design loads. Predicted design loads based on the campaign data are close to those based on the summary data discussed in a separate study.

Empirical Wind Turbine Load Distributions Using Field Data

2007 ◽  
Author(s):  
P. Agarwal ◽  
L. Manuel
Keyword(s):  
Wind Speed ◽  
Wind Turbine ◽  
Field Data ◽  
Offshore Wind ◽  
Full Time ◽  
Return Periods ◽  
Load Distributions ◽  
Design Loads ◽  
Summary Data

In the design of land-based or offshore wind turbines for ultimate limit states, long-term loads associated with return periods on the order of the service life (20 years, usually) must be estimated. This requires statistical extrapolation from turbine loads data that may be obtained by simulation or by field tests. The present study illustrates such extrapolation that uses field data from the Blyth offshore wind farm in the United Kingdom, where a 2MW wind turbine was instrumented, and environment and loads data were recorded. From this measurement campaign, the loads data available are in two different formats: as ten-minute statistics (referred to as “summary” data) and as full time series (referred to as “campaign” data). The characteristics of the site and environment and, hence, of the turbine response as well are strikingly different for wind regimes associated with onshore winds (winds from sea to land) and offshore winds (those from land to sea). The loads data (here, only the mudline bending moment is studied) at the Blyth site are hence separated depending on wind regime. By integrating load distributions conditional on the environment with the relative likelihood of the different environmental conditions, long-term loads associated with specified return periods can be derived. This is achieved here using the peak-over-threshold method based on campaign data but derived long-term loads are compared with similar estimates based on the summary data. Offshore winds are seen to govern the long-term loads at the site. Though the influence of wave heights on turbine long-term loads is smaller than that of wind speed, there is possible resonance of tower dynamics induced by the waves; still, to first order, it is largely the wind speed and turbulence intensity that control the design loads. Predicted design loads based on the campaign data are close to those based on the summary data discussed in a separate study.

The Influence of the Joint Wind-Wave Environment on Offshore Wind Turbine Support Structure Loads

2008 ◽  
Vol 130 (3) ◽  
Author(s):  
Puneet Agarwal ◽  
Lance Manuel
Keyword(s):  
Wind Turbine ◽  
Wind Turbines ◽  
Environmental Conditions ◽  
Field Data ◽  
Probabilistic Approach ◽  
Offshore Wind ◽  
Offshore Wind Turbines ◽  
Design Loads ◽  
Wind Regimes

Our objective here is to establish long-term loads for offshore wind turbines using a probabilistic approach. This can enable one to estimate design loads for a prescribed level of return period, generally on the order of 20–50years for offshore wind turbines. In a probabilistic approach, one first needs to establish “short-term” distributions of the load random variable(s) conditional on the environment; this is achieved either by using simulation or field measurements. In the present study, we use field data from the Blyth offshore wind farm in the United Kingdom, where a 2MW wind turbine was instrumented, and environment and load data were recorded. The characteristics of the environment and, hence, that of the turbine response at the site are strikingly different for wind regimes associated with different wind directions. Here, we study the influence of such contrasting environmental (wind) regimes and associated waves on long-term design loads. The field data, available as summary statistics, are limited in the sense that not all combinations of environmental conditions likely to be experienced by the turbine over its service life are represented in the measurements. Using the available data, we show how distributions for random variables describing the environment (i.e., wind and waves) and the turbine load of interest (i.e., the mudline bending moment) can be established. By integrating load distributions, conditional on the environment with the relative likelihood of different environmental conditions, long-term (extreme/ultimate) loads associated with specified return periods can be derived. This is demonstrated here by carefully separating out the data in different wind direction sectors that reflect contrasting wind (and accompanying wave) characteristics in the ocean environment. Since the field data are limited, the derived long-term design loads have inherent uncertainty associated with them; we investigate this uncertainty in such derived loads using bootstrap techniques.

Long-Term Extreme Load Prediction of Spar and Semisubmersible Floating Wind Turbines Using the Environmental Contour Method

2016 ◽  
Vol 138 (2) ◽  
Author(s):  
D. Karmakar ◽  
Hasan Bagbanci ◽  
C. Guedes Soares
Keyword(s):  
Wind Turbine ◽  
Wind Turbines ◽  
Contour Method ◽  
Return Periods ◽  
Extreme Loads ◽  
Floating Wind Turbine ◽  
Extreme Load ◽  
Design Loads ◽  
Offshore Floating Wind Turbine

The prediction of extreme loads for the offshore floating wind turbine is analyzed based on the inverse reliability technique. The inverse reliability approach is in general used to establish the design levels associated with the specified probability of failure. The present study is performed using the environmental contour (EC) method to estimate the long-term joint probability distribution of extreme loads for different types of offshore floating wind turbines. The analysis is carried out in order to predict the out-of-plane bending moment (OoPBM) loads at the blade root and tower base moment (TBM) loads for a 5 MW offshore floating wind turbine of different floater configuration. The spar-type and semisubmersible type offshore floating wind turbines are considered for the analysis. The FAST code is used to simulate the wind conditions for various return periods and the design loads of various floating wind turbine configurations. The extreme and operation situation of the spar-type and semisubmersible type offshore floating wind turbine are analyzed using one-dimensional (1D) and two-dimensional (2D)-EC methods for different return periods. The study is useful to predict long-term design loads for offshore wind turbines without requiring excessive computational effort.

Simulation of Offshore Wind Turbine Response for Extreme Limit States

2007 ◽  
Author(s):  
P. Agarwal ◽  
L. Manuel
Keyword(s):  
Wind Turbine ◽  
Environmental Conditions ◽  
Response Variability ◽  
Offshore Wind ◽  
Offshore Wind Turbine ◽  
Threshold Method ◽  
Conditional Response ◽  
Extreme Loads ◽  
Design Loads

When interest is in estimating long-term design loads for an offshore wind turbine using simulation, statistical extrapolation is the method of choice. While the method itself is rather well-established, simulation effort can be intractable if uncertainty in predicted extreme loads and efficiency in the selected extrapolation procedure are not specifically addressed. Our aim in this study is to address these questions in predicting blade and tower extreme loads based on stochastic response simulations of a 5 MW offshore turbine. We illustrate the use of the peak-over-threshold method to predict long-term extreme loads. To derive these long-term loads, we employ an efficient inverse reliability approach which is shown to predict reasonably accurate long-term loads when compared to the more expensive direct integration of conditional load distributions for different environmental (wind and wave) conditions. Fundamental to the inverse reliability approach is the issue of whether turbine response variability conditional on environmental conditions is modeled in detail or whether only gross conditional statistics of this conditional response are included. We derive design loads for both these cases, and demonstrate that careful inclusion of response variability not only greatly influences long-term design load predictions but it also identifies different design environmental conditions that bring about these long-term loads compared to when response variability is only approximately modeled. As we shall see, for this turbine, a major source of response variability for both the blade and tower arises from blade pitch control actions due to which a large number of simulations is required to obtain stable distribution tails for the turbine loads studied.

Long-Term Reliability Analysis of a Spar Buoy-Supported Floating Offshore Wind Turbine

2011 ◽  
Author(s):  
A. Sultania ◽  
L. Manuel
Keyword(s):  
Wind Speed ◽  
Wind Turbine ◽  
Reliability Analysis ◽  
Wave Height ◽  
Wind Turbines ◽  
Return Period ◽  
Random Variables ◽  
Offshore Wind ◽  
Floating Platform

Most offshore wind turbines constructed to date have support structures for the turbine towers that extend to the seabed. Such bottom-supported turbines are confined to shallow waters closer to the shore. Sites farther offshore provide a better wind resource (i.e., stronger wind and less turbulence) while also reducing concerns related to visual impact and noise. However, in deeper waters, bottom-supported turbines are less economical. Wind turbines mounted atop floating platforms are, thus, being considered for deepwater sites. Several floating platform concepts are being considered; they differ mainly in how they provide stability to counter the large mass of the rotor-nacelle assembly located high above the water. One of these alternative concepts is a spar buoy floating platform with a deep draft structure and a low center of gravity, below the center of buoyancy. The reliability analysis of a spar-supported 5MW wind turbine based on stochastic simulation is the subject of this study. Environmental data from a selected deepwater reference site are employed in the numerical studies. Using time-domain simulations, the dynamic behavior of the coupled platform-turbine system is studied; statistics of tower and rotor loads as well as platform motions are estimated and critical combinations of wind speed and wave height identified. Long-term loads associated with a 50-year return period are estimated using statistical extrapolation based on loads derived from the simulations. Inverse reliability procedures that seek appropriate load fractiles for the underlying random variables consistent with the target return period are employed; these include use of: (i) the 2D Inverse First-Order Reliability Method (FORM) where an extreme load is selected at its median level (conditional on a derived critical wind speed and wave height combination); and (ii) the 3D Inverse FORM where variability in the environmental and load random variables is fully represented to derive the 50-year load.

scholarly journals Parametric Models for Estimating Wind Turbine Fatigue Loads for Design

2001 ◽  
Vol 123 (4) ◽  
pp. 346-355 ◽  
Author(s):  
Lance Manuel ◽  
Paul S. Veers ◽  
Steven R. Winterstein
Keyword(s):  
Wind Speed ◽  
Wind Turbine ◽  
Turbulence Intensity ◽  
International Standards ◽  
Statistical Moments ◽  
Average Wind Speed ◽  
Data Set ◽  
Load Distributions ◽  
Average Wind

International standards for wind turbine certification depend on finding long-term fatigue load distributions that are conservative with respect to the state of knowledge for a given system. Statistical models of loads for fatigue application are described and demonstrated using flap and edge blade-bending data from a commercial turbine in complex terrain. Distributions of rainflow-counted range data for each ten-minute segment are characterized by parameters related to their first three statistical moments (mean, coefficient of variation, and skewness). Quadratic Weibull distribution functions based on these three moments are shown to match the measured load distributions if the non-damaging low-amplitude ranges are first eliminated. The moments are mapped to the wind conditions with a two-dimensional regression over ten-minute average wind speed and turbulence intensity. With this mapping, the short-term distribution of ranges is known for any combination of average wind speed and turbulence intensity. The long-term distribution of ranges is determined by integrating over the annual distribution of input conditions. First, we study long-term loads derived by integration over wind speed distribution alone, using standard-specified turbulence levels. Next, we perform this integration over both wind speed and turbulence distribution for the example site. Results are compared between standard-driven and site-driven load estimates. Finally, using statistics based on the regression of the statistical moments over the input conditions, the uncertainty (due to the limited data set) in the long-term load distribution is represented by 95% confidence bounds on predicted loads.

scholarly journals Dynamic Loads and Response of a Spar Buoy Wind Turbine with Pitch-Controlled Rotating Blades: An Experimental Study

Energies ◽  
2021 ◽  
Vol 14 (12) ◽  
pp. 3598
Author(s):  
Sara Russo ◽  
Pasquale Contestabile ◽  
Andrea Bardazzi ◽  
Elisa Leone ◽  
Gregorio Iglesias ◽  
...  
Keyword(s):  
Wind Speed ◽  
Wind Turbine ◽  
Degrees Of Freedom ◽  
Large Scale ◽  
Laboratory Data ◽  
Nonlinear Behavior ◽  
Offshore Wind ◽  
Small Scale ◽  
Wave Steepness ◽  
Design Factor

New large-scale laboratory data are presented on a physical model of a spar buoy wind turbine with angular motion of control surfaces implemented (pitch control). The peculiarity of this type of rotating blade represents an essential aspect when studying floating offshore wind structures. Experiments were designed specifically to compare different operational environmental conditions in terms of wave steepness and wind speed. Results discussed here were derived from an analysis of only a part of the whole dataset. Consistent with recent small-scale experiments, data clearly show that the waves contributed to most of the model motions and mooring loads. A significant nonlinear behavior for sway, roll and yaw has been detected, whereas an increase in the wave period makes the wind speed less influential for surge, heave and pitch. In general, as the steepness increases, the oscillations decrease. However, higher wind speed does not mean greater platform motions. Data also indicate a significant role of the blade rotation in the turbine thrust, nacelle dynamic forces and power in six degrees of freedom. Certain pairs of wind speed-wave steepness are particularly unfavorable, since the first harmonic of the rotor (coupled to the first wave harmonic) causes the thrust force to be larger than that in more energetic sea states. The experiments suggest that the inclusion of pitch-controlled, variable-speed blades in physical (and numerical) tests on such types of structures is crucial, highlighting the importance of pitch motion as an important design factor.

scholarly journals Long-term changes in offshore wind power density and wind turbine capacity factor in the Iberian Peninsula (1900–2010)

Energy ◽  
2021 ◽  
Vol 226 ◽  
pp. 120364
Author(s):  
Sheila Carreno-Madinabeitia ◽  
Gabriel Ibarra-Berastegi ◽  
Jon Sáenz ◽  
Alain Ulazia
Keyword(s):  
Wind Turbine ◽  
Iberian Peninsula ◽  
Wind Power ◽  
Power Density ◽  
Capacity Factor ◽  
Offshore Wind ◽  
Offshore Wind Power ◽  
Long Term Changes ◽  
Turbine Capacity

Comparison of Spar and Semisubmersible Floater Concepts of Offshore Wind Turbines Using Long-Term Analysis

2015 ◽  
Vol 137 (6) ◽  
Author(s):  
Hasan Bagbanci ◽  
D. Karmakar ◽  
C. Guedes Soares
Keyword(s):  
Wind Turbine ◽  
Wind Turbines ◽  
Transfer Functions ◽  
Probability Distributions ◽  
Offshore Wind ◽  
Short Term ◽  
Offshore Wind Turbines ◽  
Floating Wind Turbine ◽  
Offshore Floating Wind Turbine

The long-term probability distributions of a spar-type and a semisubmersible-type offshore floating wind turbine response are calculated for surge, heave, and pitch motions along with the side-to-side, fore–aft, and yaw tower base bending moments. The transfer functions for surge, heave, and pitch motions for both spar-type and semisubmersible-type floaters are obtained using the fast code and the results are also compared with the results obtained in an experimental study. The long-term predictions of the most probable maximum values of motion amplitudes are used for design purposes, so as to guarantee the safety of the floating wind turbines against overturning in high waves and wind speed. The long-term distribution is carried out using North Atlantic wave data and the short-term floating wind turbine responses are represented using Rayleigh distributions. The transfer functions are used in the procedure to calculate the variances of the short-term responses. The results obtained for both spar-type and semisubmersible-type offshore floating wind turbine are compared, and the study will be helpful in the assessments of the long-term availability and economic performance of the spar-type and semisubmersible-type offshore floating wind turbine.

Long-Term Dynamic Monitoring of an Offshore Wind Turbine

2013 ◽  
pp. 253-267 ◽  
Author(s):  
Christof Devriendt ◽  
Filipe Magalhães ◽  
Mahmoud El Kafafy ◽  
Gert De Sitter ◽  
Álvaro Cunha ◽  
...  
Keyword(s):  
Wind Turbine ◽  
Offshore Wind ◽  
Dynamic Monitoring ◽  
Offshore Wind Turbine
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