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.

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.

Investigations of Unsteady Aerodynamics of an Offshore Floating Wind Turbine With Platform Motions Using Dual-Sliding Method

2020 ◽  
Author(s):  
Xiaodong Wang ◽  
Zhaoliang Ye ◽  
Ziwen Chen ◽  
Yize Guo ◽  
Yujun Qiao
Keyword(s):  
Wind Turbine ◽  
Wind Turbines ◽  
Aerodynamic Performance ◽  
Offshore Wind ◽  
Sliding Mesh ◽  
Unsteady Aerodynamic ◽  
Floating Wind Turbine ◽  
Mesh Method ◽  
Offshore Floating Wind Turbine ◽  
Platform Motions

Abstract Offshore wind energy developed rapidly in recent years. Due to the platform motions causing by ocean waves, the aerodynamics of floating offshore wind turbines (FOWT) show strong unsteady characters than onshore wind turbines. The widely used methods to investigate the unsteady aerodynamic performance of wind turbine are Blade Element Momentum (BEM) and Free-Vortex Wake (FVW) methods. The accuracy of these two methods strongly depend on empirical formula or correction models. However, for dynamics motions of wind turbine, there is still a lack of accurate models. CFD simulations using overset or dynamic mesh methods also have been used for FOWT aerodynamic investigations. However, the mesh deforming or reconstruction methods are usually suitable for small movement of wind turbine blade. In this paper, a dual-sliding mesh method is employed to simulate the unsteady aerodynamic characters of an offshore floating wind turbine with supporting platform motions using Unsteady Reynolds Averaged Navier-Stokes (URANS) simulations. Both rotor rotation and platform motions are treated as rigid angular motions. The relative motion and data exchange were simulated using sliding mesh method. The NREL 5MW reference wind turbine with platform pitching and rolling motions are considered. The pitching and rolling motions of floating platform are simplified in the form of a prescribed sinusoidal function. Different conditions with two amplitudes and two frequencies of pitching and rolling motions were investigated. URANS were performed with full structured mesh for wind turbine rotor using commercial software FLUENT. The platform motions were set using User Defined Function (UDF). Transitional Shear Stress Turbulence (T-SST) model was employed. The simulation results were compared with BEM method and FVW method results. Both steady status and dynamic pitching processes are investigated. The variations of wind turbine aerodynamic load, as well as the aerodynamic character of airfoils at different spanwise positions, were obtained and analyzed in detail. The simulations results show that the platform pitching introduce remarkable influence on the wind turbine aerodynamic performance. The platform pitching has much larger influence on the wind turbine power and thrust than the platform rolling. The dual-sliding mesh method shows potentials to investigation the dynamic process with multiple rigid motions.

Probabilistic Analysis of LIST Data for the Estimation of Extreme Design Loads for Wind Turbine Components*†

2003 ◽  
Vol 125 (4) ◽  
pp. 531-540 ◽  
Author(s):  
M. D. Pandey ◽  
H. J. Sutherland
Keyword(s):  
Wind Turbine ◽  
Sampling Error ◽  
Test List ◽  
Structural Data ◽  
Value Theory ◽  
Extreme Value ◽  
Sampling Errors ◽  
Extreme Loads ◽  
Design Loads

The robust estimation of wind turbine design loads for service lifetimes of 30 to 50 years that are based on limited field measurements is a challenging problem. Estimating the long-term load distribution involves the integration of conditional distributions of extreme loads over the mean wind speed and turbulence intensity distributions. However, the accuracy of the statistical extrapolation can be sensitive to both model and sampling errors. Using measured inflow and structural data from the Long Term Inflow and Structural Test (LIST) program, this paper presents a comparative assessment of extreme loads using three distributions: namely, the Gumbel, Weibull and Generalized Extreme Value distributions. The paper uses L-moments, in place of traditional product moments, with the purpose of reducing the sampling error. The paper discusses the effects of modeling and sampling errors and highlights the practical limitations of extreme value theory.

Guideline for Offshore Floating Wind Turbine Structures

2010 ◽  
Author(s):  
Knut O. Ronold ◽  
Vigleik L. Hansen ◽  
Marte Godvik ◽  
Einar Landet ◽  
Erik R. Jo̸rgensen ◽  
...  
Keyword(s):  
Wind Turbine ◽  
Wind Turbines ◽  
Wind Farms ◽  
Oil And Gas Industry ◽  
Offshore Wind ◽  
Offshore Wind Turbine ◽  
Technical Requirements ◽  
Floating Wind Turbine ◽  
Floating Offshore Wind Turbines ◽  
Offshore Floating Wind Turbine

Floating offshore wind turbines is a field undergoing major development. Several companies and research institutes worldwide are engaged in research programs, pilot projects and even planning of commercial floating wind farms. Developing standards for design of floating wind turbine structures and a framework for prevailing rules are crucial and necessary for the industry to continue to grow. Det Norske Veritas (DNV) is an international provider of offshore standards for both the oil and gas industry and the wind energy industry. The standard DNV-OS-J101 “Design of Offshore Wind Turbine Structures” provides principles, technical requirements and guidance for design, construction and in-service inspection of offshore wind turbine structures. As a first step towards updating this standard to fully cover floating wind turbine structures, a DNV Guideline for Offshore Floating Wind Turbines has been established. This development is based on identification of current floating wind turbine concepts and the guideline includes an evaluation of what is required to make DNV-OS-J101 suitable for floating wind turbine structures. This paper presents the highlights of the new DNV Guideline for Offshore Floating Wind Turbine Structures.

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.

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.

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.

Fatigue Damage to the Spar-Type Offshore Floating Wind Turbine Under Blade Pitch Controller Faults

2014 ◽  
Author(s):  
Mahmoud Etemaddar ◽  
Elaheh Vahidian ◽  
Otto Skjåstad
Keyword(s):  
Wind Turbine ◽  
Fatigue Damage ◽  
Wind Turbines ◽  
Pitch Angle ◽  
Offshore Wind ◽  
Offshore Wind Turbines ◽  
Composite Blade ◽  
Floating Wind Turbine ◽  
Offshore Floating Wind Turbine ◽  
Blade Pitch Angle

The safety and reliability margin of offshore floating wind turbines need to be higher than that of onshore wind turbines due to larger environmental loads and higher operational and maintenance costs for offshore wind turbines compared to onshore wind turbines. However rotor cyclic loads coupled with 6 DOFs motions of the substructure, amplifies the fatigue damage in offshore floating wind turbines. In general a lower fatigue design factor is used for offshore wind turbines compared to that of the stationary oil and gas platforms. This is because the consequence of a failure in offshore wind turbines in general is lower than that of the offshore oil and gas platforms. In offshore floating wind turbines a sub-system fault in the electrical system and blade pitch angle controller also induces additional fatigue loading on the wind turbine structure. In this paper effect of selected controller system faults on the fatigue damage of an offshore floating wind turbine is investigated, in a case which fault is not detected by a fault detection system due to a failure in the fault detection system or operator decided to continue operation under fault condition. Two fault cases in the blade pitch angle controller of the NREL 5MW offshore floating wind turbine are modeled and simulated. These faults include: bias error in the blade pitch angle rotary encoder and valve blockage or line disconnection in the blade pitch angle actuator. The short-term fatigue damage due to these faults on the composite blade root, steel low-speed shaft, tower bottom and hub are calculated and compared with the fatigue damage under normal operational conditions considering same environmental conditions for both cases. This comparison shows that how risky is to work under the fault conditions which could be useful for wind turbine operators. The servo-hydro-aeroelastic code HAWC2 is used to simulate the time domain responses of the spar-type offshore floating wind turbine under normal and faulty operational conditions. The rain-flow cycle counting method is used to calculate the load cycles under normal operational and fault conditions. The short term fatigue damage to the composite blade root and steel structures are calculated for 6-hour reference period. The bi-linear Goodman diagram and a linear SN curve are used to estimate the fatigue damage to the composite blade root and the steel structures respectively. Moreover the fatigue damage for different mean wind speeds, sea states and fault amplitudes are calculated to figure out the region of wind speeds operation with the highest risk of damage.

Extreme Response Prediction of Offshore Wind Turbine Using Inverse Reliability Technique

2015 ◽  
Author(s):  
D. Karmakar ◽  
C. Guedes Soares
Keyword(s):  
Wind Turbine ◽  
Bending Moment ◽  
Response Prediction ◽  
Computational Effort ◽  
Offshore Wind ◽  
Contour Method ◽  
Offshore Wind Turbine ◽  
Floating Wind Turbine ◽  
Extreme Response ◽  
Design Loads

In the present study, the environmental contour method is applied for predicting out-of-plane bending moment loads at the blade root and tower base moment loads for 5MW offshore floating wind turbine of spar-type, DeepCWind and WindFloat semi-submersible floater configuration. FAST code is used to simulate the wind conditions for various return periods and a brief comparison on the design loads of the floating wind turbine for I-D, 2-D and 3-D environmental contour method is analyzed. In addition, a brief comparison of design loads with the spar-type, DeepCWind and WindFloat semi-submersible floater is discussed. The study is helpful to improve the turbine design load estimates and is useful in predicting accurate long-term design loads for wind turbines without requiring excessive computational effort.

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