Fatigue Life Analysis of Offshore Wind Turbine Support Structures in an Offshore Wind Farm

2018 ◽  
Author(s):  
Bryan Nelson ◽  
Yann Quéméner
Keyword(s):  
Wind Turbine ◽  
Wind Turbines ◽  
Wind Farm ◽  
The Body ◽  
Offshore Wind ◽  
Offshore Wind Turbine ◽  
Analysis Tool ◽  
Support Structures ◽  
Offshore Wind Farm ◽  
Actuator Disk

This study evaluated, by time-domain simulations, the fatigue lives of several jacket support structures for 4 MW wind turbines distributed throughout an offshore wind farm off Taiwan’s west coast. An in-house RANS-based wind farm analysis tool, WiFa3D, has been developed to determine the effects of the wind turbine wake behaviour on the flow fields through wind farm clusters. To reduce computational cost, WiFa3D employs actuator disk models to simulate the body forces imposed on the flow field by the target wind turbines, where the actuator disk is defined by the swept region of the rotor in space, and a body force distribution representing the aerodynamic characteristics of the rotor is assigned within this virtual disk. Simulations were performed for a range of environmental conditions, which were then combined with preliminary site survey metocean data to produce a long-term statistical environment. The short-term environmental loads on the wind turbine rotors were calculated by an unsteady blade element momentum (BEM) model of the target 4 MW wind turbines. The fatigue assessment of the jacket support structure was then conducted by applying the Rainflow Counting scheme on the hot spot stresses variations, as read-out from Finite Element results, and by employing appropriate SN curves. The fatigue lives of several wind turbine support structures taken at various locations in the wind farm showed significant variations with the preliminary design condition that assumed a single wind turbine without wake disturbance from other units.

scholarly journals Correlations of power output fluctuations in an offshore wind farm using high-resolution SCADA data

2021 ◽  
Vol 6 (4) ◽  
pp. 997-1014
Author(s):  
Janna Kristina Seifert ◽  
Martin Kraft ◽  
Martin Kühn ◽  
Laura J. Lukassen
Keyword(s):  
Wind Turbine ◽  
Wind Turbines ◽  
Power Output ◽  
Wind Farm ◽  
Offshore Wind ◽  
Offshore Wind Farm ◽  
Flow Conditions ◽  
Output Fluctuations ◽  
Power Difference ◽  
Time Correlations

Abstract. Space–time correlations of power output fluctuations of wind turbine pairs provide information on the flow conditions within a wind farm and the interactions of wind turbines. Such information can play an essential role in controlling wind turbines and short-term load or power forecasting. However, the challenges of analysing correlations of power output fluctuations in a wind farm are the highly varying flow conditions. Here, we present an approach to investigate space–time correlations of power output fluctuations of streamwise-aligned wind turbine pairs based on high-resolution supervisory control and data acquisition (SCADA) data. The proposed approach overcomes the challenge of spatially variable and temporally variable flow conditions within the wind farm. We analyse the influences of the different statistics of the power output of wind turbines on the correlations of power output fluctuations based on 8 months of measurements from an offshore wind farm with 80 wind turbines. First, we assess the effect of the wind direction on the correlations of power output fluctuations of wind turbine pairs. We show that the correlations are highest for the streamwise-aligned wind turbine pairs and decrease when the mean wind direction changes its angle to be more perpendicular to the pair. Further, we show that the correlations for streamwise-aligned wind turbine pairs depend on the location of the wind turbines within the wind farm and on their inflow conditions (free stream or wake). Our primary result is that the standard deviations of the power output fluctuations and the normalised power difference of the wind turbines in a pair can characterise the correlations of power output fluctuations of streamwise-aligned wind turbine pairs. Further, we show that clustering can be used to identify different correlation curves. For this, we employ the data-driven k-means clustering algorithm to cluster the standard deviations of the power output fluctuations of the wind turbines and the normalised power difference of the wind turbines in a pair. Thereby, wind turbine pairs with similar power output fluctuation correlations are clustered independently from their location. With this, we account for the highly variable flow conditions inside a wind farm, which unpredictably influence the correlations.

Feasibility study of offshore wind turbine substructures for southwest offshore wind farm project in Korea

2015 ◽  
Vol 74 ◽  
pp. 406-413 ◽  
Author(s):  
Wei Shi ◽  
Jonghoon Han ◽  
Changwan Kim ◽  
Daeyong Lee ◽  
Hyunkyoung Shin ◽  
...  
Keyword(s):  
Wind Turbine ◽  
Feasibility Study ◽  
Wind Farm ◽  
Offshore Wind ◽  
Offshore Wind Turbine ◽  
Offshore Wind Farm

Progress on the Development of a Holistic Coupled Model of Dynamics for Offshore Wind Farms: Phase I — Aero-Hydro-Servo-Elastic Model, With Drive Train Model, for a Single Wind Turbine

2018 ◽  
Author(s):  
Z. Lin ◽  
D. Cevasco ◽  
M. Collu
Keyword(s):  
Wind Turbine ◽  
Failure Mode ◽  
Wind Turbines ◽  
Wind Farm ◽  
Failure Modes ◽  
Coupled Model ◽  
Offshore Wind ◽  
Offshore Wind Turbine ◽  
Elastic Model ◽  
Offshore Wind Turbines

Currently, around 1500 offshore wind turbines are operating in the UK, for a total of 5.4GW, with further 3GW under construction, and 13GW consented. Until now, the focus of the research on offshore wind turbines has been mainly on how to minimise the CAPEX, but Operation and maintenance (O&M) can represent up to 39% of the lifetime costs of an offshore wind farm, due mainly to the high cost of the assets and the harsh environment, limiting the access to these assets in a safe mode. The present work is a part of a larger project, called HOME Offshore (www.homeoffshore.org), and it has as aim an advanced interpretation of the fault mechanisms through a holistic multiphysics modelling of the wind farm. The first step (presented here) toward achieving this aim consists of two main tasks: first of all, to identify and rank the most relevant failure modes within a wind farm, identifying the component, its mode of failure, and the relative environmental conditions. Then, to assess (for each failure mode) how the full-order, nonlinear model of dynamics used to represent the dynamics of the wind turbine can be reduced in order, such that is less computationally expensive (and therefore more suitable to be scaled up to represent multiple wind turbines), but still able to capture and represent the relevant dynamics linked with the inception of the chosen failure mode. A methodology to rank the failure modes is presented, followed by an approach to reduce the order of the Aero-Hydro-Servo-Elastic (AHSE) model of dynamics adopted. The results of the proposed reduced-order models are discussed, comparing it against the full-order coupled model, and taking as case study a fixed offshore wind turbine (monopile) in gearbox failure condition.

Site-Specific Design Optimization of 1.5–2.0 MW Wind Turbines

2001 ◽  
Vol 123 (4) ◽  
pp. 296-303 ◽  
Author(s):  
Peter Fuglsang ◽  
Kenneth Thomsen
Keyword(s):  
Wind Turbine ◽  
Wind Turbines ◽  
Wind Farm ◽  
Offshore Wind ◽  
Offshore Wind Farm ◽  
Load Prediction ◽  
Specific Design ◽  
Site Specific ◽  
Cost Of Energy ◽  
Fatigue Loads

A method is presented for site-specific design of wind turbines where cost of energy is minimized. A numerical optimization algorithm was used together with an aeroelastic load prediction code and a cost model. The wind climate was modeled in detail including simulated turbulence. Response time series were calculated for relevant load cases, and lifetime equivalent fatigue loads were derived. For the fatigue loads, an intelligent sensitivity analysis was used to reduce computational costs. Extreme loads were derived from statistical response calculations of the Davenport type. A comparison of a 1.5 MW stall regulated wind turbine in normal onshore flat terrain and in an offshore wind farm showed a potential increase in energy production of 28% for the offshore wind farm, but also significant increases in most fatigue loads and in cost of energy. Overall design variables were optimized for both sites. Compared to an onshore optimization, the offshore optimization increased swept area and rated power whereas hub height was reduced. Cost of energy from manufacture and installation for the offshore site was reduced by 10.6% to 4.6¢. This reduction makes offshore wind power competitive compared with today’s onshore wind turbines. The presented study was made for one wind turbine concept only, and many of the involved sub models were based on simplified assumptions. Thus there is a need for further studies of these models.

Installation Vessel and Method for Offshore Wind Turbine in Ultra-Shallow Water

2010 ◽  
Author(s):  
Huiqu Fan ◽  
Jinbao Lin ◽  
Qingsong Shi
Keyword(s):  
Wind Turbine ◽  
Shallow Water ◽  
Wind Turbines ◽  
Wind Farm ◽  
Offshore Wind ◽  
Offshore Wind Turbine ◽  
Wind Speeds ◽  
Total Investment ◽  
Key Issues ◽  
Turbine Installation

Compared to onshore wind turbines, offshore wind turbines take advantage of wind speeds which are more constant and stronger than those on land. Since many large electricity load centers are located near coastline in China, larger wind turbines can be installed closer to these areas to supply energy in a more economical way. Wind turbine transportation and installation are key issues for offshore wind farm construction, especially for large size turbine installation in ultra-shallow water like intertidal zone with water depth less than 5m. The traditional installation vessels with large design drafts are likely to be trapped in shallow water zones. It is usually impossible to carry out turbine installation in shallow water. This paper presents a set of innovative installation vessel concept and corresponding methods for ultra-shallow water zone include ultra-shallow draft crane vessel and ultra-shallow draft barge. The main purpose is to simplify the installation procedures and reduce total investment.

Framework for Risk-Based Inspection of an Offshore Wind Farm

2013 ◽  
Author(s):  
Z. Guédé ◽  
B. Bigourdan ◽  
A. Rouhan ◽  
J. Goyet ◽  
P. Renard
Keyword(s):  
Fatigue Crack ◽  
Wind Turbine ◽  
Wind Turbines ◽  
Wind Farm ◽  
Computational Effort ◽  
Offshore Wind ◽  
Structural Detail ◽  
Inspection Planning ◽  
Offshore Wind Farm ◽  
Set Up

In the present paper, a framework for Risk-Based Inspection planning is set up for a park of wind turbines taking into account the fact that only a sample of wind turbines is inspected at the scheduled inspection dates. A risk-based strategy is proposed to select the wind turbines to inspect, which significantly reduces the computational effort required by a crude application of Risk-Based Inspection analysis. The proposed framework is illustrated on a simple example of a wind farm where the failure of a wind turbine is driven by the fatigue crack of one of its critical structural detail.

scholarly journals A Coupled CFD/Multibody Dynamics Analysis Tool for Offshore Wind Turbines With Aeroelastic Blades

2017 ◽  
Author(s):  
Yuanchuan Liu ◽  
Qing Xiao ◽  
Atilla Incecik
Keyword(s):  
Wind Turbine ◽  
Multibody Dynamics ◽  
Wind Turbines ◽  
Large Scale ◽  
Turbine Blades ◽  
Offshore Wind ◽  
Offshore Wind Turbine ◽  
Analysis Tool ◽  
Dynamics Analysis ◽  
Offshore Wind Turbines

Aero-elasticity is an important issue for modern large scale offshore wind turbines with long slender blades. The behaviour of deformable turbine blades influences the structure stress and thus the sustainability of blades under large unsteady wind loads. In this paper, we present a fully coupled CFD/MultiBody Dynamics analysis tool to examine this problem. The fluid flow around the turbine is solved using a high-fidelity CFD method while the structural dynamics of flexible blades is predicted using an open source code MBDyn, in which the flexible blades are modelled via a series of beam elements. Firstly, a flexible cantilever beam is simulated to verify the developed tool. The NREL 5 MW offshore wind turbine is then studied with both rigid and flexible blades to analyse the aero-elastic influence on the wind turbine structural response and aerodynamic performance. Comparison is also made against the publicly available data.

An opportunistic maintenance strategy for offshore wind turbine based on accessibility evaluation

2019 ◽  
Vol 44 (5) ◽  
pp. 455-468
Author(s):  
Xie Lubing ◽  
Rui Xiaoming ◽  
Li Shuai ◽  
Hu Xin
Keyword(s):  
Wind Turbine ◽  
Preventive Maintenance ◽  
Wind Farm ◽  
Weather Conditions ◽  
Offshore Wind ◽  
Offshore Wind Turbine ◽  
Maintenance Strategy ◽  
Offshore Wind Farm ◽  
Opportunistic Maintenance ◽  
Operation And Maintenance

The maintenance costs of offshore wind turbines operated under the irregular, non-stationary conditions limit the development of offshore wind power industry. Unlike onshore wind farms, the weather conditions (wind and waves) have greater impacts on the operation and maintenance of offshore wind farm. Accessibility is a key factor related to the operation and maintenance of offshore wind turbine. Considering the impact of weather conditions on the maintenance activities, the Markov method and dynamic time window are applied to represent the weather conditions, and an index used to evaluate the maintenance accessibility is then proposed. As the wind turbine is a multi-component complex system, this article uses the opportunistic maintenance strategy to optimize the preventive maintenance age and opportunistic maintenance age for the main components of the wind turbine. Taking the minimum expectation cost as objective function, this strategy integrates the maintenance work of the key components. Finally, an offshore wind farm is taken for simulation case study of this strategy; the results showed that the maintenance cost of opportunistic maintenance strategy is 10% lower than that of the preventive maintenance strategy, verifying the effectiveness of the opportunistic maintenance.

scholarly journals Global offshore wind turbine dataset

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Ting Zhang ◽  
Bo Tian ◽  
Dhritiraj Sengupta ◽  
Lei Zhang ◽  
Yali Si
Keyword(s):  
Environmental Impact ◽  
Wind Turbine ◽  
Wind Turbines ◽  
Wind Farm ◽  
Wind Farms ◽  
Google Earth ◽  
Green Energy ◽  
Offshore Wind ◽  
Validation Dataset ◽  
Offshore Wind Turbine

AbstractOffshore wind farms are widely adopted by coastal countries to obtain clean and green energy; their environmental impact has gained an increasing amount of attention. Although offshore wind farm datasets are commercially available via energy industries, records of the exact spatial distribution of individual wind turbines and their construction trajectories are rather incomplete, especially at the global level. Here, we construct a global remote sensing-based offshore wind turbine (OWT) database derived from Sentinel-1 synthetic aperture radar (SAR) time-series images from 2015 to 2019. We developed a percentile-based yearly SAR image collection reduction and autoadaptive threshold algorithm in the Google Earth Engine platform to identify the spatiotemporal distribution of global OWTs. By 2019, 6,924 wind turbines were constructed in 14 coastal nations. An algorithm performance analysis and validation were performed, and the extraction accuracies exceeded 99% using an independent validation dataset. This dataset could further our understanding of the environmental impact of OWTs and support effective marine spatial planning for sustainable development.

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