scholarly journals Investigation of Dynamic Loads in Wind Turbine Drive Trains Due to Grid and Power Converter Faults

Energies ◽  
2021 ◽  
Vol 14 (24) ◽  
pp. 8542
Author(s):  
Julian Röder ◽  
Georg Jacobs ◽  
Tobias Duda ◽  
Dennis Bosse ◽  
Fabian Herzog
Keyword(s):  
Wind Turbine ◽  
High Speed ◽  
Power Converter ◽  
Wind Turbine Gearbox ◽  
Wind Turbine Gearbox Bearings ◽  
Grid Connection ◽  
Drive Trains ◽  
Electrical Faults ◽  
Doubly Fed ◽  
Component Loading

Electrical faults can lead to transient and dynamic excitations of the electromagnetic generator torque in wind turbines. The fast changes in the generator torque lead to load oscillations and rapid changes in the speed of rotation. The combination of dynamic load reversals and changing rotational speeds can be detrimental to gearbox components. This paper shows, via simulation, that the smearing risk increases due to the electrical faults for cylindrical roller bearings on the high speed shaft of a wind turbine research nacelle. A grid fault was examined for the research nacelle with a doubly fed induction generator concept. Furthermore, a converter fault was analyzed for the full size converter concept. Both wind turbine grid connection concepts used the same mechanical drive train. Thus, the mechanical component loading was comparable. During the grid fault, the risk of smearing increased momentarily by a maximum of around 1.8 times. During the converter fault, the risk of smearing increased by around 4.9 times. Subsequently, electrical faults increased the risk of damage to the wind turbine gearbox bearings, especially on the high speed stage.

Roller-Raceway Slip Simulations of Wind Turbine Gearbox Bearings Using Dynamic Bearing Model

2010 ◽  
Author(s):  
Young Sup Kang ◽  
Ryan D. Evans ◽  
Gary L. Doll
Keyword(s):  
Wind Turbine ◽  
High Speed ◽  
Roller Bearing ◽  
Operating Conditions ◽  
Critical Parameters ◽  
Wind Turbine Gearbox ◽  
Wind Turbine Gearbox Bearings ◽  
Area Reduction ◽  
Cylindrical Roller Bearing ◽  
Six Degree Of Freedom

A six degree of freedom dynamic bearing model (DBM) has been used to simulate roller-raceway slip for a cylindrical roller bearing used in an intermediate shaft location of a wind turbine gearbox. The DBM simulates the motion of bearing components such as an inner raceway, a cage, and cylindrical rollers. Radial internal clearance and operating conditions such as load and speed were varied in order to identify the most critical parameters governing roller-raceway slip. The results indicate that significant slip occurs during rapid transient accelerations and decelerations, but these high slip conditions decay to a much lower level of slip at steady state. The results also demonstrate that extreme slip occurs for low load and high speed conditions because of concomitant contact area reduction and traction loss at the roller-raceway interfaces.

scholarly journals Development of a wind turbine gearbox virtual load sensor using multibody simulation and artificial neural networks

2021 ◽  
Author(s):  
Baher Azzam ◽  
Ralf Schelenz ◽  
Björn Roscher ◽  
Abdul Baseer ◽  
Georg Jacobs
Keyword(s):  
Time Series ◽  
Wind Turbine ◽  
High Speed ◽  
Time Series Data ◽  
Development Trend ◽  
Series Data ◽  
Ann Model ◽  
Wind Turbine Gearbox ◽  
Virtual Sensor ◽  
Artificial Neural

AbstractA current development trend in wind energy is characterized by the installation of wind turbines (WT) with increasing rated power output. Higher towers and larger rotor diameters increase rated power leading to an intensification of the load situation on the drive train and the main gearbox. However, current main gearbox condition monitoring systems (CMS) do not record the 6‑degree of freedom (6-DOF) input loads to the transmission as it is too expensive. Therefore, this investigation aims to present an approach to develop and validate a low-cost virtual sensor for measuring the input loads of a WT main gearbox. A prototype of the virtual sensor system was developed in a virtual environment using a multi-body simulation (MBS) model of a WT drivetrain and artificial neural network (ANN) models. Simulated wind fields according to IEC 61400‑1 covering a variety of wind speeds were generated and applied to a MBS model of a Vestas V52 wind turbine. The turbine contains a high-speed drivetrain with 4‑points bearing suspension, a common drivetrain configuration. The simulation was used to generate time-series data of the target and input parameters for the virtual sensor algorithm, an ANN model. After the ANN was trained using the time-series data collected from the MBS, the developed virtual sensor algorithm was tested by comparing the estimated 6‑DOF transmission input loads from the ANN to the simulated 6‑DOF transmission input loads from the MBS. The results show high potential for virtual sensing 6‑DOF wind turbine transmission input loads using the presented method.

scholarly journals Investigation of Roller Sliding in Wind Turbine Gearbox High-Speed-Shaft Bearings

2019 ◽  
Author(s):  
David Vaes ◽  
Yi Guo ◽  
Pietro Tesini ◽  
Jonathan A Keller
Keyword(s):  
Wind Turbine ◽  
High Speed ◽  
Wind Turbine Gearbox

Comparison of Blind Diagnostic Indicators for Condition Monitoring of Wind Turbine Gearbox Bearings

2021 ◽  
Author(s):  
Junyu Qi ◽  
Alexandre Mauricio ◽  
Konstantinos Gryllias
Keyword(s):  
Wind Turbine ◽  
Condition Monitoring ◽  
Wind Turbines ◽  
Fossil Fuels ◽  
Conditional Entropy ◽  
Approximate Entropy ◽  
Permutation Entropy ◽  
Wind Turbine Gearbox ◽  
Data Set ◽  
Wind Turbine Gearbox Bearings

Abstract Under the pressure of climate change, renewable energy gradually replaces fossil fuels and plays nowadays a significant role in energy production. The O&M costs of wind turbines may easily reach up to 25% of the total leverised cost per kWh produced over the lifetime of the turbine for a new unit. Manufacturers and operators try to reduce O&M by developing new turbine designs and by adopting condition monitoring approaches. One of the most critical assembly of wind turbines is the gearbox. Gearboxes are designed to last till the end of asset's lifetime, according to the IEC 61400-4 standards but a recent study indicated that gearboxes might have to be replaced as early as 6.5 years. A plethora of sensor types and signal processing methodologies have been proposed in order to accurately detect and diagnose the presence of a fault but often the gearbox is equipped with a limited number of sensors and a simple global diagnostic indicator is demanded, being capable to detect globally various faults of different components. The scope of this paper is the application and comparison of a number of blind global diagnostic indicators which are based on Entropy, on Negentropy, on Sparsity and on Statistics. The performance of the indicators is evaluated on a wind turbine data set with two different bearing faults. Among the different diagnostic indicators Permutation entropy, Approximate entropy, Samples entropy, Fuzzy entropy, Conditional entropy and Wiener entropy achieve the best results detecting blindly the two failure events.

Loading and Design Parameter Uncertainty in the Dynamics and Performance of High-Speed-Parallel-Helical Stage of a Wind Turbine Gearbox

2013 ◽  
Author(s):  
Fisseha M. Alemayehu ◽  
Stephen Ekwaro-Osire
Keyword(s):  
Wind Turbine ◽  
Parameter Uncertainty ◽  
System Reliability ◽  
Design Parameter ◽  
High Speed ◽  
Probability Of Failure ◽  
Wind Turbine Gearbox ◽  
Input Shaft ◽  
Input Variables ◽  
And Performance

The Wind Turbine Gearboxes (WTGs) are highly subjected to variable torsional and non-torsional loads. In addition, the manufacturing and assembly process of these devices results in uncertainty in the system. These gearboxes are reported to fail in their early life of operation, within three to seven years as opposed to the expected twenty years of operation. Their downtime and maintenance process is the most costly of any failure of subassembly of wind turbines. The objective of this work is to perform a probabilistic multibody dynamic analysis (PMBDA) of the high-speed-parallel-helical stage of the gearbox of wind turbine that considers uncertainty of generator side torque loading and the input shaft speed, assembly errors and design parameter uncertainty. System reliability, probability of failure, and probabilistic sensitivities of all the input variables towards several performance functions have been measured and conclusions have been drawn. PMBDA has demonstrated a new dimension of design and installation of wind turbine gearboxes than traditional deterministic approach. In addition to revealing system reliability or under-performance through probability of failure, the method will also help designers to consider certain variables critically through the sensitivity results.

Study of stabilty analysis of a grid connected Doubly fed induction generator based on wind energy Application

2016 ◽  
Vol 3 (2) ◽  
pp. 305 ◽  
Author(s):  
Ghulam sarwar Kaloi ◽  
Jie Wang ◽  
Mazhar H Baloch
Keyword(s):  
Wind Turbine ◽  
Operating Conditions ◽  
Induction Generator ◽  
Doubly Fed Induction Generator ◽  
Grid Connection ◽  
Wind Turbine System ◽  
Space Modeling ◽  
Point Of Common Coupling ◽  
Doubly Fed ◽  
The Stability

<p><em> </em><em>     </em>The present paper formulates the state space modeling of doubly fed induction generator (DFIG) based wind turbine system for the purpose of the stability analysis. The objective of this study is to discuss the various modes of operation of the DFIG system under different operating conditions such as voltage sags with reference to variable wind speed and grid connection. The proposed control methodology exploits the potential of the DFIG scheme to avoid that grid voltage unbalances compromise the machine operation, and to compensate voltage unbalances at the point of common coupling (PCC), preventing adverse effects on loads connected next to the PCC. This methodology uses the rotor side converter (RSC) to control the stator current injected through the machine and the GSC to control the stator voltage to minimize the electromagnetic torque oscillations. Extensive simulation results on a 2MW DFIG wind turbine system illustrate the enhanced system performance and verify the effectiveness of the controller.</p>

Application of Wavelet De-Noising in Fault Diagnosis of Wind Turbine Gearboxes

2012 ◽  
Vol 562-564 ◽  
pp. 1091-1094 ◽  
Author(s):  
Hai Jiang Kou ◽  
Hui Qun Yuan ◽  
Xiao Yu Zhao
Keyword(s):  
Wind Turbine ◽  
High Speed ◽  
Fault Location ◽  
Time Domain Analysis ◽  
Fault Detection And Diagnosis ◽  
Wind Turbine Gearbox ◽  
Stationary Noise ◽  
Wind Turbine System ◽  
Detection And Diagnosis ◽  
The Time Domain

Fault detection and diagnosis of a wind turbine gearbox are important to ensure the reliability and useful life of the wind turbine system. In this paper, an experimental test in wind turbine gearboxes is carried out to obtain faulted information which consists of response random non-stationary noise and the additional response due to failure. An approach, using wavelet de-noising method, is proposed for removing non-stationary noise from the recorded signals. The time domain analysis and frequency analysis are used to diagnose the fault location of the machine accurately. It is shown that wavelet de-noising method provides a better correction than conventional method in order to remove non-stationary noise. Diagnosis results indicate that the high-speed shaft of wind turbine gearboxes has a serious imbalance.

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