Wind Turbine Doubly-Fed Asynchronous Machine Diagnosis Defects—State of the Art

Hammouchi, Fatima El; Menzhi, Lamia El; Saâd, Abdallah

doi:10.12783/dteees/icnerr2017/13314

Cited by 5 publications

(6 citation statements)

References 2 publications

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“…Rotor turbine blades, a gearbox, a generator, and a power electronics converter are the main components of the DFIG machine. Research by Hammouchi et al [6] GSC, DC link, and rotor-side converter (RSC) are the components that make up the power converter module. The common connection is used to couple the stator, GSC, and DFIG to the grid.…”

Section: Doubly Fed Induction Generatormentioning

confidence: 99%

“…Zhang et al [5] proposes an image array for recognizing the defect in turbine blades using a neural network. Finally, it diagnoses faults in the field-oriented control of doubly fed induction generators (DFIG) using frequency spectrum and Lissajous curves [6]. Han et al [7] combined the unstable streamlined and WT dynamic models to compute a unique response based on beam theory in a typhoon for 6 MW and 2 MW WTs.…”

Section: Introductionmentioning

confidence: 99%

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Blade imbalance fault identification in doubly fed induction generator through current signature analysis using wavelet transform

Kushwaha,

Yadav,

Maurya

2024

Bulletin EEI

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Using wind turbines (WTs) equipped with doubly fed induction generators (DFIG) is a popular technology for generating renewable energy. To ensure safe operation, prompt maintenance, and better operational reliability, the induction generator used in wind energy must be monitored. In this paper, an analysis is carried out on stator currents of the DFIG machine in a wind farm to identify any blade imbalances in the wind farm. A fault characteristics extraction analysis is carried out on the machine stator currents to detect the fault in the system. Firstly, the mathematical equation of the DFIG blade unbalanced stator current is generated using the DFIG model. Secondly, Park's Transformation is used to modify the stator's 3-phase current. Further, by evaluating the feature frequency amplitude variation in the squared signal by doing a spectral analysis on the stator current vector's squared signal. Lastly, a Simulink model for the DFIG is developed. The suggested approach analyses the fault signal of the imbalanced blade fault at various wind velocities. The outcomes show that the suggested method for diagnosing impeller imbalance faults can successfully locate the fault.

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Section: Doubly Fed Induction Generatormentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Blade imbalance fault identification in doubly fed induction generator through current signature analysis using wavelet transform

Kushwaha,

Yadav,

Maurya

2024

Bulletin EEI

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“…Indeed, regardless of the rotor power magnitude and direction, the GSC has to keep the dc-link capacitor voltage at a set value and to guarantee a converter operation with unity power factor (zero reactive power) [9]. We introduced sum of different sinusoidal signals: varied amplitudes and frequencies in order to create wind speed model in Matlab Simulink as showed in the figure 2, which reflects approximately a recorded wind speed in Moroccan wind farms [10]. We assume that frictions are neglected and with the use of equations presented in previous paper [11], the wind turbine Matlab Simulink model is created.…”

Section: Wind Turbine Modelingmentioning

confidence: 99%

DFIG Defects Diagnosis Method for Wind Energy Conversion Chain

Hammouchi¹,

Menzhi²,

Saâd³

2019

Adv. sci. technol. eng. syst. j.

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The research consists on developing method to diagnose electrical defects affecting wind turbine doubly-fed induction generator DFIG which constitutes a crucial part of wind energy conversion chain. First off all, we create a model of a non-defected wind conversion system based on mathematical equations introduced in Matlab Simulink. Then, we apply an indirect vector control stator field orientation in order to increase wind energy performance. With the aim of diagnosing the defects attacking wind turbine generator, we propose a method based on grouping of fast Fourier transform spectral analysis and Lissajous curves performed to generator stator and rotor currents. This diagnosis technique is applied to wind turbine in normal operation (non-defected generator) in order to have a reliable reference data for asynchronous generator behaviour. However, connected to the grid, wind turbine generator is affected by various faults occurring in electrical power networks. Therefore, the diagnosis method is applied also to a defected generator. Considering diversity of grid defects, we deal in the current paper with open stator supplying phases and open rotor feeding phases due to rotor side converter legs opening. Indeed, this diagnosis method allows diagnosing generator defects type and severity by comparing the resulting frequency spectrum analysis and Lissajous curves under abnormal condition operating to reference data obtained in case of non-defected generator. So, our proposed method contributes to DFIG defects identification and anticipation. The simulations had been accomplished using Matlab Simulink. These results proved the efficiency and effectiveness of the proposed DFIG diagnosis method for wind energy conversion chain.

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Section: Introductionmentioning

confidence: 99%

Risk analysis and prevention in computer security in institutional servers, a systematic review of the literature

Namo-Ochoa,

Portilla-Cosar,

Sierra-Liñan

et al. 2024

Bulletin EEI

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In recent years, computer attacks on the server infrastructure in organizations have been increasing, and the pandemic of covid-19 and remote work have been the main causes for this massive wave of large-scale attacks, small businesses are especially vulnerable because to optimizing resources they leave aside the cyber security in their network infrastructure. The present research is a systematic review that compiles 58 articles where policies, techniques, and infrastructure for the prevention of threats in enterprise servers have been implemented and raised, these articles have been collected from major databases such as IEEE Xplore, SAGE, Science Direct, Scopus, and IOP Publishing. The results show that one of the most effective methods in preventing communications between institutional servers is public key infrastructure/SSL-TLS encryption. Most research claims that it is the most effective method as it provides a central certifier and manages the certificates for the servers allowing each of the modules or attachments within the infrastructure to identify and validate other members and to proceed with the encryption of network traffic, Finally, a security implementation model is proposed.

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Wind Turbine Doubly-Fed Asynchronous Machine Diagnosis Defects—State of the Art

Cited by 5 publications

References 2 publications

Blade imbalance fault identification in doubly fed induction generator through current signature analysis using wavelet transform

Blade imbalance fault identification in doubly fed induction generator through current signature analysis using wavelet transform

DFIG Defects Diagnosis Method for Wind Energy Conversion Chain

Risk analysis and prevention in computer security in institutional servers, a systematic review of the literature

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