scholarly journals Seismic Fragility Analysis of Monopile Offshore Wind Turbines under Different Operational Conditions

Energies ◽  
2017 ◽  
Vol 10 (7) ◽  
pp. 1037 ◽  
Author(s):  
Renjie Mo ◽  
Haigui Kang ◽  
Miao Li ◽  
Xuanlie Zhao
Keyword(s):  
Wind Turbines ◽  
Offshore Wind ◽  
Fragility Analysis ◽  
Seismic Fragility ◽  
Operational Conditions ◽  
Offshore Wind Turbines

Statistical Estimation of Extreme Loads for the Design of Offshore Wind Turbines during Non-Operational Conditions

2015 ◽  
Vol 39 (6) ◽  
pp. 629-640 ◽  
Author(s):  
Gordon M. Stewart ◽  
Matthew A. Lackner ◽  
Sanjay R. Arwade ◽  
Spencer Hallowell ◽  
Andrew T. Myers
Keyword(s):  
Wind Turbines ◽  
Statistical Estimation ◽  
Offshore Wind ◽  
Operational Conditions ◽  
Offshore Wind Turbines ◽  
Extreme Loads

scholarly journals Fatigue Stress Estimation for Submerged and Sub-Soil Welds of Offshore Wind Turbines on Monopiles Using Modal Expansion

Energies ◽  
2021 ◽  
Vol 14 (22) ◽  
pp. 7576
Author(s):  
Maximilian Henkel ◽  
Wout Weijtjens ◽  
Christof Devriendt
Keyword(s):  
Wind Turbines ◽  
Wind Farm ◽  
Measurement Data ◽  
Offshore Wind ◽  
Strain History ◽  
Fe Model ◽  
Modal Expansion ◽  
Operational Conditions ◽  
Offshore Wind Turbines ◽  
Farm Operators

The design of monopile foundations for offshore wind turbines is most often driven by fatigue. With the foundation price contributing to the total price of a turbine structure by more than 30%, wind farm operators seek to gain knowledge about the amount of consumed fatigue. Monitoring concepts are developed to uncover structural reserves coming from conservative designs in order to prolong the lifetime of a turbine. Amongst promising concepts is a wide array of methods using in-situ measurement data and extrapolating these results to desired locations below water surface and even seabed using models. The modal decomposition algorithm is used for this purpose. The algorithm obtains modal amplitudes from acceleration and strain measurements. In the subsequent expansion step these amplitudes are expanded to virtual measurements at arbitrary locations. The algorithm uses a reduced order model that can be obtained from either a FE model or measurements. In this work, operational modal analysis is applied to obtain the required stress and deflection shapes for optimal validation of the method. Furthermore, the measurements that are used as input for the algorithms are constrained to measurements from the dry part of the substructure. However, with subsoil measurement data available from a dedicated campaign, even validation for locations below mud-line is possible. After reconstructing strain history in arbitrary locations on the substructure, fatigue assessment over various environmental and operational conditions is carried out. The technique is found capable of estimating fatigue with high precision for locations above and below seabed.

Pitch Angle Control of Floating Offshore Wind Turbines by H∞ Control

2014 ◽  
Vol 134 (8) ◽  
pp. 1096-1103 ◽  
Author(s):  
Sho Tsujimoto ◽  
Ségolène Dessort ◽  
Naoyuki Hara ◽  
Keiji Konishi
Keyword(s):  
Wind Turbines ◽  
Pitch Angle ◽  
Offshore Wind ◽  
Offshore Wind Turbines ◽  
Floating Offshore Wind Turbines

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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