scholarly journals Extended Environmental Contour Methods for Long-Term Extreme Response Analysis of Offshore Wind Turbines1

2020 ◽  
Vol 142 (5) ◽  
Author(s):  
Xiaolu Chen ◽  
Zhiyu Jiang ◽  
Qinyuan Li ◽  
Ye Li ◽  
Nianxin Ren
Keyword(s):  
Turbulence Intensity ◽  
Offshore Structures ◽  
Offshore Wind ◽  
Contour Method ◽  
Offshore Wind Turbine ◽  
Response Analysis ◽  
Modified Method ◽  
Extreme Response ◽  
Wind Turbulence

Abstract Environmental contour method is an efficient method for predicting the long-term extreme response of offshore structures. The traditional environmental contour is obtained using the joint distribution of mean wind speed, significant wave height, and spectral peak period. To improve the accuracy of traditional environmental contour method, a modified method was proposed considering the non-monotonic aerodynamic behavior of offshore wind turbines. Still, the modified method assumes constant wind turbulence intensity. In this paper, we extend the existing environmental contour methods by considering the wind turbulence intensity as a stochastic variable. The 50-year extreme responses of a monopile-based offshore wind turbine are compared using the extended environmental contour methods and the full long-term method. It is found that both the environmental contour method and the modified environmental contour method, with the wind turbulence intensity included as an individual variable, give more accurate predictions compared with those without. Using the full long-term method as a benchmark, this extended approach could reduce the nonconservatism of the environmental contour method and conservatism of the modified environmental contour method. This approach is effective under wind-dominated or combined wind-wave loading conditions, but may not be as important for wave-dominated conditions.

scholarly journals Effect of Wind Turbulence on Extreme Load Analysis of an Offshore Wind Turbine

2019 ◽  
Author(s):  
Xiaolu Chen ◽  
Zhiyu Jiang ◽  
Qinyuan Li ◽  
Ye Li
Keyword(s):  
Wind Turbine ◽  
Turbulence Intensity ◽  
Environmental Conditions ◽  
Dynamic Responses ◽  
Offshore Wind ◽  
Contour Method ◽  
Offshore Wind Turbine ◽  
Extreme Response ◽  
Wind Turbulence ◽  
The Impact

Abstract Evaluation of dynamic responses under extreme environmental conditions is important for the structural design of offshore wind turbines. Previously, a modified environmental contour method has been proposed to estimate extreme responses. In the method, the joint distribution of environmental variables near the cut-out wind speed is used to derive the critical environmental conditions for a specified return period, and the turbulence intensity (TI) of wind is assumed to be a deterministic value. To address more realistic wind conditions, this paper considers the turbulence intensity as a stochastic variable and investigates the impact on the modified environmental contour. Aerodynamic simulations are run over a range of mean wind speeds at the hub height from 9–25 m/s and turbulence levels between 9%–15%. Dynamic responses of a monopile offshore wind turbine under extreme conditions were studied, and the importance of considering the uncertainties associated with wind turbulence is highlighted. A case of evaluating the extreme response for 50-year environmental contour is given as an example of including TI as an extra variant in environmental contour method. The result is compared with traditional method in which TI is set as a constant of 15%. It shows that taking TI into consideration based on probabilistic method produces a lower extreme response prediction.

Joint Distribution of Environmental Condition at Five European Offshore Sites for Design of Combined Wind and Wave Energy Devices

2015 ◽  
Vol 137 (3) ◽  
Author(s):  
Lin Li ◽  
Zhen Gao ◽  
Torgeir Moan
Keyword(s):  
Renewable Energy ◽  
Wave Energy ◽  
Environmental Data ◽  
Offshore Wind ◽  
Response Analysis ◽  
Energy Devices ◽  
Joint Distributions ◽  
Wave Parameters ◽  
Extreme Response

The design of wind turbines requires information about joint data for wind and wave conditions. Moreover, combining offshore wind and wave energy facilities is a potential way to reduce the cost of offshore wind farms. To design combined offshore renewable energy concepts, it is important to choose sites where both wind and wave energy resources are substantial. This paper deals with joint environmental data for five European offshore sites which serve as basis for the analysis and comparison of combined renewable energy concepts developed in the EU FP7 project—MARINA Platform. The five sites cover both shallow and deep water, with three sites facing the Atlantic Ocean and two sites in the North Sea. The long-term joint distributions of wind and wave parameters are presented for these sites. Simultaneous hourly mean wind and wave hindcast data from 2001 to 2010 are used as a database. The joint distributions are modeled by fitting analytical distributions to the hindcast data. The long-term joint distributions can be used to estimate the wind and wave power output from each combined concept and to estimate the fatigue lifetime of the structure. The marginal distributions of wind and wave parameters are also provided. Based on the joint distributions, contour surfaces are established for combined wind and wave parameters for which the probability of exceedance corresponds to a return period of 50 years. The design points on the 50-year contour surfaces are suggested for extreme response analysis of combined concepts.

Short-term extreme response analysis of a jacket supporting an offshore wind turbine

Wind Energy ◽  
2012 ◽  
Vol 17 (1) ◽  
pp. 87-104 ◽  
Author(s):  
Nilanjan Saha ◽  
Zhen Gao ◽  
Torgeir Moan ◽  
Arvid Naess
Keyword(s):  
Wind Turbine ◽  
Offshore Wind ◽  
Offshore Wind Turbine ◽  
Response Analysis ◽  
Short Term ◽  
Extreme Response

scholarly journals Effects of Simulation Length and Flexible Foundation on Long-Term Response Extrapolation of a Bottom-Fixed Offshore Wind Turbine

2021 ◽  
pp. 1-36
Author(s):  
David Barreto ◽  
Madjid Karimirad ◽  
Arturo Ortega
Keyword(s):  
Wind Turbine ◽  
Bending Moment ◽  
Offshore Wind ◽  
Contour Method ◽  
Offshore Wind Turbine ◽  
Modeling Uncertainty ◽  
Flexible Foundation ◽  
Extreme Responses ◽  
Term Response

Abstract This paper deals with statistical and modeling uncertainty on the estimation of long-term extrapolated extreme responses in a monopile offshore wind turbine. The statistical uncertainty is addressed by studying the effect of simulation length. Modeling uncertainty is explored by evaluating the effects of considering a rigid and flexible foundation. The soil's flexibility is taking into account by considering the improved apparent fixity method. To identify the most relevant environmental conditions, the modified environmental contour method is used. The analysis focuses on the fore-aft shear force (FASF) and the fore-aft bending moment (FABM) at the mudline. The results show that using a simulation length of 10-min, does not provide sufficient accuracy. It was found that for the FASF, simulation lengths of at least 30-min are required to achieve an accuracy of about +/-5%. For the FABM, it was found that both the extrapolations made with 20-min and 30-min simulations achieved similar levels of accuracy of about 20%. Meanwhile, the results obtained from 10-min simulations reached deviations of about 40%. Finally, from the comparison made between a rigid and flexible foundation, it was found that the extrapolated responses exhibit maximum deviations up to around 5% and 10% for the FASF and the FABM, respectively. Also, for the FABM, it was observed that the consideration of a flexible foundation causes the critical wind speed to shift from 16.5 m/s (rigid) to 18 m/s (flexible).

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.

scholarly journals Maintenance Planning of Offshore Wind Turbine Using Condition Monitoring Information

2009 ◽  
Author(s):  
Jose´ G. Rangel-Rami´rez ◽  
John D. So̸rensen
Keyword(s):  
Condition Monitoring ◽  
Wind Turbines ◽  
Wind Farm ◽  
Offshore Structures ◽  
Offshore Wind ◽  
Offshore Wind Turbine ◽  
Maintenance Planning ◽  
Offshore Wind Turbines ◽  
Inspection And Maintenance ◽  
Monitoring Information

Deterioration processes such as fatigue and corrosion are typically affecting offshore structures. To “control” this deterioration, inspection and maintenance activities are developed. Probabilistic methodologies represent an important tool to identify the suitable strategy to inspect and control the deterioration in structures such as offshore wind turbines (OWT). Besides these methods, the integration of condition monitoring information (CMI) can optimize the mitigation activities as an updating tool. In this paper, a framework for risk-based inspection and maintenance planning (RBI) is applied for OWT incorporating CMI, addressing this analysis to fatigue prone details in welded steel joints at jacket or tripod steel support structures for offshore wind turbines. The increase of turbulence in wind farms is taken into account by using a code-based turbulence model. Further, additional modes t integrate CMI in the RBI approach for optimal planning of inspection and maintenance. As part of the results, the life cycle reliabilities and inspection times are calculated, showing that earlier inspections are needed at in-wind farm sites. This is expected due to the wake turbulence increasing the wind load. With the integration of CMI by means Bayesian inference, a slightly change of first inspection times are coming up, influenced by the reduction of the uncertainty and harsher or milder external agents.

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