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This paper compares the buffeting responses of offshore wind turbines subjected to recently observed hurricane models with responses from IEC 61400-3 extreme load condition. For this purpose, first, the recent observations on hurricane turbulence models were discussed. Next, hurricane wind and wave fields were simulated based on the Saffir-Simpson hurricane wind scale. Later, a new formulation for addressing unsteady wind forces on the tower and modified NREL-FAST package was implemented to analyze structure-wind-wave-soil interaction of the NREL-5 MW wind turbine during hurricane. Finally, by using the short term structural responses, an extreme value analysis based on direct integration method with peak over threshold (POT) approach was carried out to compare the results with IEC 61400-3 recommendations. Results showed that for design of the tower and blades subjected to hurricane buffeting forces, the IEC 61400-3 recommendations for turbine class I are overestimated and underestimated respectively to be used for class S.

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The 13th Americas Conference on Wind Engineering (13ACWE)

Gainesville, Florida USA, May 21-24, 2017

Comparison of Loads from IEC 61400-3 Extreme Conditions with

Loads from Recently Observed Hurricane Models

Gholamreza Amirinia, Sungmoon Jung

Department of Civil and Environmental Engineering, Florida A&M University – Florida State

University, Tallahassee, United States

ABSTRACT

This paper compares the buffeting responses of offshore wind turbines subjected to recently ob-

served hurricane models with responses from IEC 61400-3 extreme load condition. For this pur-

pose, first, the recent observations on hurricane turbulence models were discussed. Next, hurricane

wind and wave fields were simulated based on the Saffir-Simpson hurricane wind scale. Later, a

new formulation for addressing unsteady wind forces on the tower and modified NREL-FAST

package was implemented to analyze structure-wind-wave-soil interaction of the NREL-5 MW

wind turbine during hurricane. Finally, by using the short term structural responses, an extreme

value analysis based on direct integration method with peak over threshold (POT) approach was

carried out to compare the results with IEC 61400-3 recommendations. Results showed that for

design of the tower and blades subjected to hurricane buffeting forces, the IEC 61400-3 recom-

mendations for turbine class I are overestimated and underestimated respectively to be used for

class S.

KEYWORDS: Offshore wind turbine, hurricane, extreme value analysis, IEC-61400-3.

1 INTRODUCTION

Many studies have been conducted to address different issues on wind turbines structural parts

subjected to regular boundary layer winds (non-hurricane winds) [1-6]; however, hurricane winds

and their effects on the structures still need more studies and observations. Thus in the last decade,

much research has been conducted in order to clarify the nature and characteristics of hurricanes,

their differences with regular high winds, and their effects on the structures [7-13].

Observations and analysis of hurricane surface winds revealed that turbulence spectrum of hurri-

cane winds differs from that of non-hurricane high winds [7, 8, 12, 14-17]. Li et al. [16] and

Caracoglia and Jones [14] showed that in the hurricane, the higher turbulence frequencies have

higher level of energy; however, Schroeder and Smith [12], Yu et al. [17], and Jung and Masters

[8] showed that hurricane spectrum has higher level of energy in low frequencies. Different turbu-

lence energy models affect structures differently, while the mean wind speed and turbulence in-

tensity are identical between models [18]. In this regard, mean responses of structures subjected

to regular high winds and hurricane winds are comparable, whereas, the buffeting responses are

different. Because of these differences in buffeting responses, conditions such as structural integ-

rity and low cycle fatigue subjected to different hurricane turbulence models should be investi-

gated.

IEC 61400-1 [19] and IEC 61400-3 [20] have recommendations for different wind turbine

classes and load cases; however, for special events such as hurricane, they introduced wind turbine

class S which the design variables should be defined by the designer. In order to compare the short

term responses of the wind turbine subjected to hurricane with IEC 61400-1 [19] and IEC 61400-

3 [20] recommendations, an extreme value analysis is necessary. Several studies has been con-

ducted on extreme value analysis which considered various methods and approaches [4, 5, 21]. By

considering the importance of new hurricane turbulence models on buffeting responses, an accu-

rate extreme value analysis is necessary for comparing the short term results with IEC 61400-3

[20] recommendations. An accurate extreme value analysis and comparison with existing recom-

mendations also assist to consider important issues in designing wind turbines class S.

This paper compares responses of offshore wind turbines subjected to recently observed hurri-

cane turbulence models with IEC 61400-3 recommendations. For this purpose, first, the recent

observations on hurricane turbulence models were discussed and compared with Kaimal spectrum

model. At next step, according to importance of recent findings about hurricane winds, hurricane

wind and wave fields were simulated based on the Saffir-Simpson hurricane wind scale. Next, the

modified NREL-FAST [22, 23] package with a new formulation for addressing unsteady wind

forces on the tower was implemented to analyze structure-wind-wave-soil interaction of the

NREL-5 MW [24] wind turbine. Finally, by using the short term structural responses, an extreme

value analysis based on direct integration method with peak over threshold (POT) approach was

carried out to compare the results with IEC 61400-1 [19] recommendations.

2 HURRICANE BOUNDARY LAYER WINDS

The wind turbulence spectrum represents the energy distribution in turbulent wind [16]. Many

studies investigated wind turbulence spectrums for non-hurricane winds [25-28]. Kaimal et al.

[26], based on series of experiments, showed that all turbulence spectrums reduce to a limited

family of curves and proposed a formula for wind spectrum as shown in eq. 1:

where    represents the normalized frequency,  is the frequency,  is the

spectral density of the longitudinal velocity fluctuation at height , and  is the standard devia-

tion of longitudinal velocity fluctuation. On the other hand, hurricane field data observations dur-

ing the last decade revealed that turbulence spectrum of the hurricane boundary layer winds is

different from those of non-hurricane winds. According to the data observed by Schroeder and

Smith [12], Yu et al. [17], Jung and Masters [8], Caracoglia and Jones [14], and Li et al. [16], the

spectral distribution of hurricane winds shows a large variability. Schroeder and Smith [12], Yu

et al. [17], and Jung and Masters [8] showed that compared to non-hurricane spectral models,

hurricane spectrums had higher energy content in low frequencies. Eq. 2 shows a formula derived

for hurricane wind turbulence spectrum [17] with high amount of energy in low frequencies:







       

   

where  is the turbulence ratio and  represents the friction velocity, and 

and  are constants proposed by Yu et al. [17] as shown in Table 1.

Table 1. Coefficients of Yu et al. (2008) spectrum

The 13th Americas Conference on Wind Engineering (13ACWE)

Gainesville, Florida USA, May 21-24, 2017

On the other hand, Li et al. [16] and Caracoglia and Jones [14] based on series of observations,

presented an opposite results that higher frequencies contained larger amount of energy rather than

low frequencies. Li et al. [16] provided spectrum models for their observation with high amount

of energy in high frequencies as:







   

Table 2 summarizes the spectrum models presented by mentioned researchers and used in this

paper. In addition, Figure 1 shows the difference between recent observed models and the spectrum

introduced by Kaimal et al. [26].

Table 2. Spectrum models summary

Schroeder and Smith [12], Yu et al.

[17], Jung and Masters [8]

Caracoglia and Jones [14], Li et al.

[16]

Figure 1. Comparison of hurricane spectrum models (over sea) and Kaimal spectrum

3 WIND BUFFETING FORCES ON WIND TURBINE

Previous studies showed that in parked condition the tower play an important role in total structural

responses and unsteady analysis of the tower resulted in more realistic responses [22, 23]. Formu-

lation of wind loading on the wind turbine tower is given in eq. 4 and eq. 5 as [29]:

     

 



   

 

          

where     

      are quasi-static forces,    are buffeting forces,    

and   are self-excited forces,  and  are longitudinal and lateral fluctuating parts of the

wind, and  and  are structural position and velocity vectors. In eq. 5 and eq. 6 it is assumed

that the main flow direction is perpendicular to the rotor plane and wind field is homogenous [29].

Aerodynamic analysis and wind tunnel tests showed that in a line-like structure, the turbulence

eddies hit the structure simultaneously [30, 31]; however, when the size of the structure increases,

the turbulence eddies may not hit the structure at the same time which corresponds to aerodynamic

unsteady forces. The aerodynamic unsteady forces can be addressed by aerodynamic admittance

function [30]. In order to address unsteady forces on the tower, previous studies used rational

functions for presenting aerodynamic admittance function [22, 23]. Figure 2 illustrates the aero-

dynamic admittance function presented by Davenport [30] compared with two terms rational func-

tion (RF) approximation (), measured rational function by Clobes and Peil [32], rectangular

prism wind tunnel tests, and measured indicial functions by Chang et al. [33].

Figure 2. Aerodynamic admittance function

4 HURRICANE WIND AND WAVE MODELING

To investigate the contribution of blades and tower under hurricane condition, the NREL 5MW

offshore monopile wind turbine [24] was selected for analysis. 60 wind field time series for each

turbulence model (each one 600s) were generated by NREL-TurbSim [34] with frequency of 10

Hz. The mean wind speeds at 10 m height were equal to 30, 40, 50,60, 70, and 80 m/s (each speed

10 time series) in order to cover five Saffir-Simpson hurricane categories [35]. In addition, wave

field was generated based on JONSWAP (Joint North Sea Wave Observation Project) spectrum

The 13th Americas Conference on Wind Engineering (13ACWE)

Gainesville, Florida USA, May 21-24, 2017

[36] by assuming 20 m water depth, 6 hours hurricane, and duration-limited wave. The wave

length,   , for each peak wave period,  , ranges from 230 m to 613 m which rep-

resents shallow water in the depth of 20 m (). Hence the maximum wave height will be

0.9 times of the water depth [37] and the maximum wave height for the considered depth was

limited to 18 m. The nonlinear wave forces due to large wind induced wave heights were computed

by the HydroDyn package [38] through a hybrid model consist of potential flow theory and Mori-

son's equation. The Saffir-Simpson wind characteristics and generated wave field is presented in

Table 3.

Table 3. Saffir-Simpson hurricane categories and modeled wind and wave field

Modeled Wind

Speed @10m (m/s)

5 EXTREME VALUE ANALYSIS

IEC 61400-3 [20] provides recommendations for extreme value analysis and long term load ex-

trapolations for different wind turbine classes; however, for special conditions such as hurricane,

it defines class S, where the values should be specified by the designer. In order to compare IEC

61400-3 [20] recommendations with recent hurricane observations, the wind turbine class I in a

low turbulence offshore region (similar to recent observations [17]) was selected. In this case, the

reference wind speed and turbulence intensity at hub height were 50 m/s and 12% respectively

[20].

In order to conduct an extreme value analysis, there are several methods such as direct integra-

tion, first order reliability method (FORM), and inverse first order reliability method (IFORM) [1,

39]. The direct integration method which is the most straight forward method can be expressed as

[39]:

        





where      is the probability that load  resulted from 10 minute simulation ex-

ceed the load value of ,   represents the cumulative distribution of load value  in the

wind speed bin , and   is the wind speed distribution. A common way for using the direct

integration method is to use the method of peak-over threshold (POT). In the POT method, a

threshold is selected and the local maxima are captured. Then the exceedance probability can be

restated as:

          





where  is the expected number of peaks above the selected threshold. According to IEC

61400-1 [19] and IEC 61400-3 [20], the 10 minutes averaging duration is standard for wind turbine

analysis. In this case, the probability to observe a load  larger than -years load,  , can be

expressed as:

           

In order to compare IEC 61400-3 [20] recommendation and results from new hurricane turbu-

lence models, the extreme wind speed model (EWM) with 50-years recurrence period (50 m/s @

hub height) was considered which reduced eq. 8 to:

6 RESULTS

Choosing an appropriate threshold and distribution for exceedance probability are important for

extreme value analysis [1, 20, 39]. The distribution representing the exceedance probability of the

local maxima in each wind speed should precisely represent the tail behavior. Figure 3 shows

observed local maxima of tower buffeting base moment with different POTs where Weibull,

lognormal, and generalized extreme value (GEV) distributions are fitted on the data (SD: Standard

Deviation). By increasing the threshold values, the POT method leads to the method of global

maxima.

The 13th Americas Conference on Wind Engineering (13ACWE)

Gainesville, Florida USA, May 21-24, 2017

Figure 3. Fitted distributions on local maxima based on different thresholds as (a) 1.4SD, (b) 2.0SD, (c) 2.5SD, and

(d) 3.0SD

The direct integration method with a POT of 1.4 ×SD [19] was applied for extreme value anal-

ysis of the tower fore-aft base and blade root edge-wise moments. Moreover, three mentioned

distributions for fitting local maxima in this section were used for the analysis. Figure 4 shows the

response extreme value analysis of the three turbulence models by assuming different distributions

compared to IEC 61400-3 [20] recommendations. At 50-years return period, by assuming Weibull

distribution for tower buffeting fore-aft moment, IEC 61400-3 [20] recommendations are larger

than resulted extreme values from all turbulence models; however, IEC 61400-3 [20] recommen-

dations are smaller than results of GEV assumption (Figure 4a, c, e). Hence, by assuming Weibull

and GEV distributions respectively, IEC 61400-3 [20] recommendations for wind turbine class I

are respectively conservative and non-conservative for designing the tower of wind turbine class

S subjected to hurricane.

Blades response extreme value analysis showed that for Kaimal et al. [26] and Model B, all

three distributions resulted in larger extreme values than IEC 61400-3 [20] recommendations (Fig-

ure 4b, f); however, for Model A, Weibull and GEV distributions resulted in smaller and larger

values than IEC 61400-3 [20] recommendations respectively (Figure 4d).

Figure 4. Extreme value analysis of fore-aft buffeting base moment (a: Kaimal et al. [26], c: Model A, e: Model B)

and blade root edge-wise moment (b: Kaimal et al. [26], d: Model A, f: Model B) using different distributions

The comparison of the different distributions for extreme value analysis showed that, Weibull

distributions has the smallest extreme values for the tower and blades. Hence the IEC 61400-3 [20]

recommendations compared to Weibull distribution results, turns in the condition for proposing

minimum changes in IEC 61400-3 [20]. By assuming Weibull distribution for local maxima, Fig-

ure 5a shows the extreme values of tower buffeting base moment for three different turbulence

models. In this case the IEC 61400-3 [20] recommendations resulted in 30%, 37%, and 18% larger

values than Kaimal et al. [26], Model A and Model B respectively. For blade root edge-wise mo-

ment, the IEC 61400-3 [20] recommendations resulted in underestimating the blade buffeting re-

sponses compared to conventional Kaimal et al. [26] model and spectrum Model B (Figure 5b).

Table 4 shows the values of tower buffeting fore-aft base moment and blade root edge-wise

moment extrapolated for 50-years return period.

Figure 5. Extreme value analysis of the (a) tower buffeting base moment, (b) blade root buffeting edge-wise moment

The 13th Americas Conference on Wind Engineering (13ACWE)

Gainesville, Florida USA, May 21-24, 2017

Table 4. 50-years return period buffeting responses for different models

Tower Buffeting base

moment (MNm)

Blade Root edge-wise

moment (MNm)

The extreme value analysis of along-wind responses depicted that by assuming Weibull distri-

bution for local maxima, for designing the tower, the IEC 61400-3 [20] recommendations for tur-

bine class I can be used for class S; however, for designing the blades subjected to hurricane, IEC

61400-3 [20] should be reconsidered.

7 CONCLUSION

This paper studied the effects of newly observed hurricane turbulence models on offshore wind

turbines by considering unsteady aerodynamic forces on the tower. The main goal was to compare

the 61400-3 [10] recommendations for wind turbine class S with hurricane forces resulted from

recent observations. For this purpose, first, the recent observations and presented turbulence mod-

els were discussed. The five Saffir-Simpson hurricane categories as well as wind induced wave

field was generated. Then. The modified NREL-FAST package to address unsteady forces on the

tower was implemented. At the end the followings were concluded:

- In order to compare the responses of short term analysis of the offshore wind turbine with

IEC 61400-3 [20] recommendations for 50-years return period, an extreme value analysis

was carried out. For the extreme value analysis, the direct integration method with peak

over threshold (POT) approach was used. The extreme value analysis of along-wind re-

sponses depicted that by assuming Weibull distribution for local maxima, for designing the

tower, the IEC 61400-3 [20] recommendations for turbine class I can be used for class S;

however, for designing the blades subjected to hurricane, IEC 61400-3 [20] should be re-

considered. On the other hand, assuming GEV distribution showed that IEC 61400-3 [20]

recommendation for turbine class I, should be revised for designing tower and blades of

turbine class S subjected to hurricane.

- The comparison of three different distributions for fitting local maxima in extreme value

analysis showed that, Weibull distribution has the smallest extreme values for tower an d

blades. Hence the IEC 61400-3 [20] recommendations compared to Weibull distribution

results, will be the condition for proposing minimum changes in IEC 61400-3 [20]. By

using the Weibull distributions, the results showed that for the tower fore-aft buffeting base

moment, the IEC 61400-3 [20] recommendations resulted in 30%, 37%, and 18% larger

values than Kaimal et al. [26], Model A and Model B respectively; however, the IEC

61400-3 [20] recommendations resulted in underestimating the blade edge-wise buffeting

responses compared to conventional Kaimal et al. [26] model and spectrum Model B.

Hence, for designing the tower for special events such as hurricane, the IEC 61400-3 [20]

recommendations for turbine class I can be used for wind turbine class S; however, for

designing the blades subjected to hurricane, IEC 61400-3 [20] should be reconsidered.

8 ACKNOWLEDGMENT

The research reported here is supported in part by the National Science Foundation CMMI Grant

1252736. Any opinions, findings, and conclusions expressed in this paper are those of the authors

and do not necessarily reflect the views of the sponsor.

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Energy Engineering. 2008; 130:031011.

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Most of the studies on wind turbine subjected to high winds, consider quasi-steady formulation for wind turbine parts. The objective of this paper is to investigate the along wind responses of a parked wind turbine subjected to hurricane forces by considering, first, the tower unsteady aerodynamics, and second, the recent observations and proposed models for hurricanes. For this purpose, quasi-steady formulation of aerodynamic forces on a parked wind turbine was modified by addressing unsteady aerodynamic effects on the wind turbine tower. A time domain approach for addressing the unsteady aerodynamics of the tower was proposed by using aerodynamic admittance function. The frequency dependent aerodynamic admittance function was addressed in time domain using rational functions (RF). This procedure was implemented in NREL-FAST package and the model was verified. In order to investigate the structural responses subjected to hurricane, the recent observations of the hurricane boundary layer winds as well as the models presented for hurricane turbulence energy were discussed. The unsteady analysis of wind turbine structure subjected to various hurricane turbulence models, resulted in the range of 29% smaller to 4.9% larger responses than quasi-steady analysis of conventional spectrum models presented in past literature and carried out by NREL-FAST module.

This paper aims to optimize the distribution of chord and twist angle of small wind turbine blade in order to maximize its Annual Energy Production (AEP). A horizontal-axis wind turbine (HAWT) blade is optimized using a calculation code based on the Blade Element Momentum (BEM) theory. A difficult task in the implementation of the BEM theory is the correct representation of the lift and drag coefficients at post-stall regime. In this research, the method based on the Viterna equations was used for extrapolating airfoil data into the post-stall regime and the results were compared with various mathematical models. Results showed the high capability of this method to predict the performance of wind turbines. Evaluation of the efficiency of wind turbine blade designed with the proposed model shows that the optimum design parameters gave rise to an increase of 8.51% in the AEP rate as compared with the corresponding manufactured operating parameters. Ó 2016 Faculty of Engineering, Alexandria University. Production and hosting by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

This study focuses on effect of unsteady aerodynamic formulation of buffeting forces on wind turbine tower during high winds. As of now, unsteady formulation have been used for analysing aerodynamic forces on wind turbine blades during operational condition. But in high wind situation where blades pitch angles are small and turbine is in parked condition, usually the effect of unsteady aerodynamic buffeting forces have been neglected. This article formulated the unsteady aerodynamic buffeting forces on wind turbine tower in a time domain framework. In this regard, the frequency dependent aerodynamic admittance function was formulated in time domain using rational functions. The comparison between unsteady formulation on wind turbine tower and conventional quasi-steady formulation showed that unsteady analysis in high winds, results in 4.9 percent decrease in fluctuating fore-aft base moment caused by buffeting forces and 3.5 percent decrease in buffeting fore-aft tower tip displacement.

Wind turbines as the structures which are designed to harness huge amount of wind energy are subjected to special loads such as high winds and hurricanes because of their heights. Hurricane wind spectrums and amount of energy content is one of the important parameters that make hurricane winds different from regular high winds. In this paper, we investigate how different spectrums of hurricane winds influence the wind turbine response, using a simplified wind turbine structure. Two different approaches for hurricane wind spectrums are cited and 30 time series based on each of these approaches are generated. In addition, 30 time series based on regular high wind spectrum are generated and applied on the structure. The results show that, for structure with high amount of natural frequency, the hurricane spectrum with higher energy in high frequencies part has more effect on the structure so it would be more conservative to use these spectrums for design. However, for low natural frequency structures like offshore floating wind turbines it would be apposite and the spectrums with high energy amount in low frequency part apply greater loads on the structure.

• Sepehr Sanaye
• Arash Hassanzadeh

The power output of a wind turbine depends on the aerodynamic and geometrical characteristic of its airfoils, and therefore, the proper airfoil design for wind turbine blades is highly important. Furthermore, due to the usage of small wind turbines within city limits, the emitted noise is also a major issue. In the present work, "XFoil" and "NAFNoise" programs were used for flow analysis around blade cross sections (airfoils) and predicting the corresponding noise emission, respectively. Multi-objective optimization was carried out for maximizing the airfoil lift-to-drag ratio (CL/CD) and minimizing the sound pressure level. With two above objective functions and by defining decision variables along with introducing physical and engineering constraints, genetic algorithm method was applied for optimization process. Moreover, 'Fuzzy Bellman-Zadeh' decision-making method was applied for selecting final optimal point from Pareto front. The results of this new method of airfoil shape analysis at various wind velocities showed about 26% average increase in CL/CD and 1.11% average decrease in noise emission in comparison with that for typical highly used S822 airfoil in small wind turbines.

• Einar Strømmen

This text book is intended for studies in structural dynamics or wind engineering, with special focus on the stochastic theory of wind induced dynamic response calculations for slender bridges or other line- like civil engineering type of structures. It contains the background assumptions and hypothesis as well as the development of the computational theory that is necessary for the prediction of wind induced fluctuating displacements and cross sectional forces. The book contains detailed and complete examples of relevant cases that are useful for the understanding and the practical application of the theory. The text is at an advanced level in the sense that it requires some knowledge of basic structural dynamics, particularly of solution procedures in a modal format.

• Arash Hassanzadeh
• Jonathan Naughton

A new design approach has been developed for wind turbine blades to be used in wind tunnel experiments that study wind turbine wakes. The approach allows wakes of small scale (2 m diameter) wind turbine rotors to simulate the important physics of wakes generated by a ``parent'' industrial scale wind turbine rotor despite the difference in size. The design approach forces the normalized normal and tangential force distributions of the small scale wind turbine blades to match those of the ``parent'' industrial scale wind turbine blades. The wake arises from the interaction between the flow and the blade, which imparts a momentum deficit and rotation to the flow due to the forces created by the blade on the flow. In addition, the wake dynamics and stability are affected by the load distribution across the blade. Thus, it is expected that matching normalized force distributions should result in similar wake structure. To independently assess the blades designed using this approach, the ``parent'' industrial scale and small scale wind turbine rotors are modeled using a free vortex wake method to study the generation and evolution of the two wakes.

• Kuangmin Gong
• Xinzhong Chen

This study presents a dynamic response analysis of operational and parked wind turbines in order to gain better understanding of the roles of wind loads on turbine blades and tower in the generation of turbine response. The results show that the wind load on the tower has a negligible effect on the blade responses of both operational and parked turbines. Its effect on the tower response is also negligible for operational turbine, but is significant for parked turbine. The tower extreme responses due to the wind loads on blades and tower of parked turbine can be estimated separately and then combined for the estimation of total tower extreme response. In current wind turbine design practice, the tower extreme response due to the wind loads on blades is often represented as a static response under an equivalent static load in terms of a concentrated force and a moment at the tower top. This study presents an improved equivalent static load model with additional distributed inertial force on tower, and introduces the square-root-of-sum-square combination rule, which is shown to provide a better prediction of tower extreme response.

During extreme tropical storm systems such as hurricanes, offshore wind turbines are required to have adequate structural integrity in parked condition and with blades pitched to feather. Such turbine states are preferred in order to mitigate loads on the turbine blades; simultaneously, yaw control is required so as to track the changing wind direction in this configuration. During a hurricane, however, it is possible that a turbine's yaw control system might operate abnormally due to damage of the control and protection system or due to loss of the electric grid and/or insufficient backup power. In earlier studies, the authors have shown that feathered blades can lead to higher tower bending moments in the side-to-side (lateral) direction rather than in the fore-aft (longitudinal) direction. In the present study, we carry out an in-depth investigation of the effect of several alternative parked configurations on an offshore turbine's response using numerical simulations with coupled wind-wave fields during a hurricane. We use these output wind-wave fields obtained from the University of Miami Coupled Model (UMCM), a fully coupled atmosphere-wave-ocean model that is used to simulate the storm and associated environmental fields and is able to represent relevant physical processes at the air-sea interface. In this study, we evaluate: (1) the effect of different nacelle yaw angles relative to the wind direction (i.e., different amounts of yaw error or misalignment); (2) the effect of different blade pitch angles; (3) the effect of different turbine parking strategies—e.g., parked and at a standstill or in an idling state; and (4) load maxima at different blade azimuthal configurations while the turbine is in a standstill state. The effects of the different turbine parked configurations on turbine response are evaluated under only wind loads first; later, wave loads are included to reflect possible joint metocean conditions likely to be encountered during a hurricane.

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Source: https://www.researchgate.net/publication/317040589_Comparison_of_Loads_from_IEC_61400-3_Extreme_Conditions_with_Loads_from_Recently_Observed_Hurricane_Models