scholarly journals Validation of Improved Sampling Concepts for Offshore Wind Turbine Fatigue Design

Energies ◽  
2019 ◽  
Vol 12 (4) ◽  
pp. 603 ◽  
Author(s):  
Clemens Hübler ◽  
Wout Weijtjens ◽  
Cristian Gebhardt ◽  
Raimund Rolfes ◽  
Christof Devriendt
Keyword(s):  
Environmental Conditions ◽  
Wind Farm ◽  
Measurement Data ◽  
Monte Carlo Sampling ◽  
Offshore Wind ◽  
Offshore Wind Turbine ◽  
Sampling Effort ◽  
Data Set ◽  
Ongoing Research ◽  
Fatigue Design

Fatigue damage is a design-driving phenomenon for substructures of offshore wind turbines. However, fatigue design based on numerical simulations is quite uncertain. One main reason for this uncertainty is scattering offshore conditions combined with a limited number of simulations (samples). According to current standards, environmental conditions are sampled using a deterministic grid of the most important environmental conditions (e.g., wind speed and direction, significant wave height, and wave period). Recently, there has been some effort to reduce the inherent uncertainty of damage calculations due to limited data by applying other sampling concepts. Still, the investigation of this uncertainty and of methods to reduce it is a subject of ongoing research. In this work, two improved sampling concepts—previously proposed by the authors and reducing the uncertainty due to limited sampling—are validated. The use of strain measurement data enables a realistic estimate of the inherent uncertainty due to limited samples, as numerical effects, etc., are excluded. Furthermore, an extensive data set of three years of data of two turbines of the Belgian wind farm Northwind is available. It is demonstrated that two previously developed sampling methods are generally valid. For a broad range of model types (i.e., input dimensions as well as degrees of non-linearity), they outperform standard sampling concepts such as deterministic grid sampling or Monte Carlo sampling. Hence, they can reduce the uncertainty while keeping the sampling effort constant, or vice versa.

scholarly journals Transient LES of an offshore wind turbine

2017 ◽  
Vol 2 (2) ◽  
pp. 603-614 ◽  
Author(s):  
Lukas Vollmer ◽  
Gerald Steinfeld ◽  
Martin Kühn
Keyword(s):  
Wind Turbine ◽  
Wind Farm ◽  
Mesoscale Model ◽  
Sampling Rate ◽  
Measurement Data ◽  
Wind Farms ◽  
Offshore Wind ◽  
Offshore Wind Turbine ◽  
Offshore Wind Farms ◽  
Synoptic Wind

Abstract. The estimation of the cost of energy of offshore wind farms has a high uncertainty, which is partly due to the lacking accuracy of information on wind conditions and wake losses inside of the farm. Wake models that aim to reduce the uncertainty by modeling the wake interaction of turbines for various wind conditions need to be validated with measurement data before they can be considered as a reliable estimator. In this paper a methodology that enables a direct comparison of modeled with measured flow data is evaluated. To create the simulation data, a model chain including a mesoscale model, a large-eddy-simulation (LES) model and a wind turbine model is used. Different setups are compared to assess the capability of the method to reproduce the wind conditions at the hub height of current offshore wind turbines. The 2-day-long simulation of the ambient wind conditions and the wake simulation generally show good agreements with data from a met mast and lidar measurements, respectively. Wind fluctuations due to boundary layer turbulence and synoptic-scale motions are resolved with a lower representation of mesoscale fluctuations. Advanced metrics to describe the wake shape and development are derived from simulations and measurements but a quantitative comparison proves to be difficult due to the scarcity and the low sampling rate of the available measurement data. Due to the implementation of changing synoptic wind conditions in the LES, the methodology could also be beneficial for case studies of wind farm performance or wind farm control.

scholarly journals Transient LES of an offshore wind turbine

2017 ◽  
Author(s):  
Lukas Vollmer ◽  
Gerald Steinfeld ◽  
Martin Kühn
Keyword(s):  
Wind Turbine ◽  
Wind Farm ◽  
Marine Boundary Layer ◽  
Sampling Rate ◽  
Measurement Data ◽  
Wind Farms ◽  
Offshore Wind ◽  
Offshore Wind Turbine ◽  
Flow Measurements ◽  
Offshore Wind Farms

Abstract. The estimation of the cost of energy of offshore wind farms has a high uncertainty, which is partly due to the lacking accuracy of information on wind conditions and wake losses inside of the farm. Wake models that aim on reducing the uncertainty by modeling the wake interaction of turbines for various wind conditions need to be validated with measurement data before they can be considered as a reliable estimator. A methodology is shown to create realistic transient wind conditions in a Large-Eddy-Simulation of a marine boundary layer interacting with an offshore wind turbine for a direct comparison of modeled with measured flow data. A mesoscale simulation is used for determining the boundary conditions of the model. The simulations of the ambient wind conditions and the wake simulation generally show a good agreement with measurements from a met mast and lidar measurements, respectively. Advanced metrics to describe the wake shape and development are derived from simulations and measurements but a quantitative comparison is difficult due to the scarcity and the low sampling rate of the available measurement data. The methodology presents a possibility to compare flow measurements with simulations. Due to the implementation of changing wind conditions in the LES it could be also beneficial for case studies of wind turbine and wind farm control.

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.

Experimental Study for SPAR Type Floating Offshore Wind Turbine With Blade-Pitch Control

2013 ◽  
Author(s):  
Toshiki Chujo ◽  
Yoshimasa Minami ◽  
Tadashi Nimura ◽  
Shigesuke Ishida
Keyword(s):  
Wind Turbine ◽  
Wind Farm ◽  
Offshore Wind ◽  
Scale Model ◽  
Offshore Wind Turbine ◽  
Experimental Proof ◽  
Pitch Control ◽  
Model Experiments ◽  
North Eastern ◽  
North Eastern Part

The experimental proof of the floating wind turbine has been started off Goto Islands in Japan. Furthermore, the project of floating wind farm is afoot off Fukushima Prof. in north eastern part of Japan. It is essential for realization of the floating wind farm to comprehend its safety, electric generating property and motion in waves and wind. The scale model experiments are effective to catch the characteristic of floating wind turbines. Authors have mainly carried out scale model experiments with wind turbine models on SPAR buoy type floaters. The wind turbine models have blade-pitch control mechanism and authors focused attention on the effect of blade-pitch control on both the motion of floater and fluctuation of rotor speed. In this paper, the results of scale model experiments are discussed from the aspect of motion of floater and the effect of blade-pitch control.

scholarly journals Unsupervised Damage Detection for Offshore Jacket Wind Turbine Foundations Based on an Autoencoder Neural Network

Sensors ◽  
2021 ◽  
Vol 21 (10) ◽  
pp. 3333
Author(s):  
Maria del Cisne Feijóo ◽  
Yovana Zambrano ◽  
Yolanda Vidal ◽  
Christian Tutivén
Keyword(s):  
Neural Network ◽  
Wind Turbine ◽  
Environmental Conditions ◽  
Wind Farms ◽  
Offshore Wind ◽  
Offshore Wind Turbine ◽  
Small Subset ◽  
Scaled Model ◽  
Vibration Data ◽  
Large Water

Structural health monitoring for offshore wind turbine foundations is paramount to the further development of offshore fixed wind farms. At present time there are a limited number of foundation designs, the jacket type being the preferred one in large water depths. In this work, a jacket-type foundation damage diagnosis strategy is stated. Normally, most or all the available data are of regular operation, thus methods that focus on the data leading to failures end up using only a small subset of the available data. Furthermore, when there is no historical precedent of a type of fault, those methods cannot be used. In addition, offshore wind turbines work under a wide variety of environmental conditions and regions of operation involving unknown input excitation given by the wind and waves. Taking into account the aforementioned difficulties, the stated strategy in this work is based on an autoencoder neural network model and its contribution is two-fold: (i) the proposed strategy is based only on healthy data, and (ii) it works under different operating and environmental conditions based only on the output vibration data gathered by accelerometer sensors. The proposed strategy has been tested through experimental laboratory tests on a scaled model.

scholarly journals Optimal Temperature-Based Condition Monitoring System for Wind Turbines

2021 ◽  
Vol 6 (4) ◽  
pp. 50
Author(s):  
Payam Teimourzadeh Baboli ◽  
Davood Babazadeh ◽  
Amin Raeiszadeh ◽  
Susanne Horodyvskyy ◽  
Isabel Koprek
Keyword(s):  
Monitoring System ◽  
Wind Turbines ◽  
Wind Farm ◽  
Measurement Data ◽  
Real Data ◽  
Offshore Wind ◽  
Risk Indicator ◽  
Real World Data ◽  
The Real ◽  
Data Driven Modeling

With the increasing demand for the efficiency of wind energy projects due to challenging market conditions, the challenges related to maintenance planning are increasing. In this paper, a condition-based monitoring system for wind turbines (WTs) based on data-driven modeling is proposed. First, the normal condition of the WTs key components is estimated using a tailor-made artificial neural network. Then, the deviation of the real-time measurement data from the estimated values is calculated, indicating abnormal conditions. One of the main contributions of the paper is to propose an optimization problem for calculating the safe band, to maximize the accuracy of abnormal condition identification. During abnormal conditions or hazardous conditions of the WTs, an alarm is triggered and a proposed risk indicator is updated. The effectiveness of the model is demonstrated using real data from an offshore wind farm in Germany. By experimenting with the proposed model on the real-world data, it is shown that the proposed risk indicator is fully consistent with upcoming wind turbine failures.

Study on the Dynamic Response for Floating Foundation of Offshore Wind Turbine

2011 ◽  
Author(s):  
Yougang Tang ◽  
Jun Hu ◽  
Liqin Liu
Keyword(s):  
Wind Turbine ◽  
Wind Farm ◽  
Dynamic Responses ◽  
Offshore Wind ◽  
Offshore Wind Turbine ◽  
Wave Load ◽  
Mooring Lines ◽  
Floating Foundation ◽  
Wind Turbine System ◽  
Sea Area

The wind resources for ocean power generation are mostly distributed in sea areas with the distance of 5–50km from coastline, whose water depth are generally over 20m. To improve ocean power output and economic benefit of offshore wind farm, it is necessary to choose floating foundation for offshore wind turbine. According to the basic data of a 600kW wind turbine with a horizontal shaft, the tower, semi-submersible foundation and mooring system are designed in the 60-meter-deep sea area. Precise finite element models of the floating wind turbine system are established, including mooring lines, floating foundation, tower and wind turbine. Dynamic responses for the floating foundation of offshore wind turbine are investigated under wave load in frequency domain.

Optimization of O&M for Offshore Wind Farms Modelling for WMTC Conferences

2015 ◽  
Author(s):  
Thomas Nivet ◽  
Ema Muk-Pavic
Keyword(s):  
Wind Farm ◽  
Wind Farms ◽  
Cost Effective ◽  
Offshore Wind ◽  
Offshore Wind Turbine ◽  
Offshore Wind Farms ◽  
Climate Conditions ◽  
Operation Analysis ◽  
Cost Effective Approach ◽  
Failure Evaluation

Offshore wind energy is one of the most upcoming sources of energy, and it is already partially replacing the fossil fuelled power production. However, offshore wind turbine technology is also associated with harsher weather environment. Indeed, it experiences more challenging wind and wave conditions, which in turn limits the vessels capabilities to access the wind farms. Additionally, with the constant rise of power utilization, improvements in the Operation Maintenance (O&M) planning are crucial for the development of large isolated offshore wind farms. Improvements in the planning of the O&M for offshore wind farms could lead to considerable reduction in costs. For this reason, the interest of this research paper is the investigation of the most cost effective approach to offshore turbine maintenance strategies. This objective is achieved by implementing a simulation approach that includes a climate conditions analysis, an operation analysis, a failure evaluation and a simulation of the repairs. This paper points out how different O&M strategies can influence the sustainability of a wind farm.

Comparison of the Fatigue Performance of Galvanised M72 Bolts With Design Standard Recommendations

2021 ◽  
Author(s):  
Carol Johnston ◽  
Matthew Doré
Keyword(s):  
Fatigue Performance ◽  
Offshore Wind ◽  
Offshore Wind Turbine ◽  
Design Codes ◽  
Design Standards ◽  
Threaded Fasteners ◽  
Fatigue Design ◽  
Standard Design ◽  
Wind Turbine Towers ◽  
Thickness Correction

Abstract Now that bolted flanges rather than grouted connections are used to join the transition piece to the monopile in offshore wind turbine towers, many large bolts are being used in applications which subject them to fatigue loads. The bolts in these ring flanges are typically M64 or M72 in size (ie 64mm of 72mm nominal diameter). The fatigue design codes, BS 7608, DNVGL-RP-C203 and Eurocode 3 do provide S-N curves for threaded fasteners, but the reference diameter in those documents is 25mm or 30mm. A thickness correction is provided, to account for larger diameter bolts, but this was originally derived by analysis of the performance of welded joints. It is unclear whether the S-N curves and the recommended thickness correction are appropriate for larger diameter threaded fasteners. The offshore wind industry usually specifies hot dip galvanised bolts, to provide some corrosion protection in the offshore environment. Again, there is uncertainty over whether the S-N curves in fatigue design standards apply to bolts with a galvanised coating. Since the fatigue design codes provide S-N curves for air, free corrosion or seawater with cathodic protection, it is also unclear which of these should be used to predict the fatigue performance of bolts with a galvanised coating. In order to provide data to address these uncertainties, hot-dip galvanised, grade 10.9, M72 bolts from two manufacturers were tested in both air and a seawater environment. In order to represent the conditions experienced by bolts in internal ring flanges, the artificial seawater was sprayed onto the bolts during testing. Tests were conducted with a mean stress corresponding to 70% of the specified minimum 0.2% proof strength of the bolts. Tests were also performed in air, on uncoated M72 bolts, and uncoated M64 bolts for comparison. The results suggest that the current thickness correction in DNVGL RP C203 and BS 7608 is appropriate for M72 bolts. The results in air from the galvanised bolts were below those from uncoated bolts. Although the galvanised results were above the thickness corrected in-air standard design curves (BS7608 Class X -20%, DNVGL Class G and DNVGL ST 0126 FAT 50), they were below the mean curves, suggesting that the performance of galvanised bolts is slightly lower than the existing recommendations.

Evaluating the Coupledness of the Aerodynamics and Hydrodynamics on the Estimation of Fatigue Damage Equivalent Load for a Floating Offshore Wind Platform

2018 ◽  
Author(s):  
Samuel Kanner ◽  
Bingbin Yu
Keyword(s):  
Fatigue Life ◽  
Fatigue Damage ◽  
Environmental Conditions ◽  
Offshore Wind ◽  
Coupled Analysis ◽  
Offshore Wind Turbine ◽  
Wave Conditions ◽  
Equivalent Load ◽  
The Waves

In this research, the estimation of the fatigue life of a semi-submersible floating offshore wind platform is considered. In order to accurately estimate the fatigue life of a platform, coupled aerodynamic-hydrodynamic simulations are performed to obtain dynamic stress values. The simulations are performed at a multitude of representative environmental states, or “bins,” which can mimic the conditions the structure may endure at a given site, per ABS Floating Offshore Wind Turbine Installation guidelines. To accurately represent the variety of wind and wave conditions, the number of environmental states can be of the order of 103. Unlike other offshore structures, both the wind and wave conditions must be accounted for, which are generally considered independent parameters, drastically increasing the number of states. The stress timeseries from these simulations can be used to estimate the damage at a particular location on the structure by using commonly accepted methods, such as the rainflow counting algorithm. The damage due to either the winds or the waves can be estimated by using a frequency decomposition of the stress timeseries. In this paper, a similar decoupled approach is used to attempt to recover the damages induced from these coupled simulations. Although it is well-known that a coupled, aero-hydro analysis is necessary in order to accurately simulate the nonlinear rigid-body motions of the platform, it is less clear if the same statement could be made about the fatigue properties of the platform. In one approach, the fatigue damage equivalent load is calculated independently from both scatter diagrams of the waves and a rose diagram of the wind. De-coupled simulations are performed to estimate the response at an all-encompassing range of environmental conditions. A database of responses based on these environmental conditions is constructed. The likelihood of occurrence at a case-study site is used to compare the damage equivalent from the coupled simulations. The OC5 platform in the Borssele wind farm zone is used as a case-study and the damage equivalent load from the de-coupled methods are compared to those from the coupled analysis in order to assess these methodologies.

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