Islanding detection method for DFIG wind turbines using artificial neural networks

Abd-Elkader, Ahmad G.; Allam, Dalia; Eldin, Sayed M.

doi:10.1016/j.ijepes.2014.04.052

Cited by 48 publications

(38 citation statements)

References 15 publications

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“…The technique measures their symmetrical components at the wind farm side and feed to an Artificial Neural Network (ANN) for islanding detection. The results show that the proposed ANN technique is able to distinguish between islanding and other events, and can detect islanding in a very fast manner [118].…”

Section: Artificial Neural Network (Ann) Based Islanding Detection Tementioning

confidence: 96%

“…Another ANN based passive islanding detection technique suitable for DFIG wind turbines based on the symmetrical components of the second harmonic of voltage and current signals is proposed in [118]. The proposed technique used second order harmonic of voltage and current measurements by processing these signals using Fourier transform.…”

Section: Artificial Neural Network (Ann) Based Islanding Detection Tementioning

confidence: 99%

See 1 more Smart Citation

Computational Intelligence based techniques for islanding detection of distributed generation in distribution network: A review

Laghari

Mokhlis

Karimi

et al. 2014

Energy Conversion and Management

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Section: Artificial Neural Network (Ann) Based Islanding Detection Tementioning

confidence: 96%

Section: Artificial Neural Network (Ann) Based Islanding Detection Tementioning

confidence: 99%

Computational Intelligence based techniques for islanding detection of distributed generation in distribution network: A review

Laghari

Mokhlis

Karimi

et al. 2014

Energy Conversion and Management

View full text Add to dashboard Cite

“…Similar work has been done with three phase current signal combined into one modal signal of a 9 MVA wind based test system in [102] to obtain 0% classification error rate. Another application of ANN in ID is found in [103]. Voltage and current signals at PCC of a wind farm power station are measured and processed through Fourier transform to extract second harmonic.…”

Section: Annmentioning

confidence: 99%

Shifting of research trends in islanding detection method - a comprehensive survey

Dutta

Sadhu

Reddy

et al. 2018

Prot Control Mod Power Syst

117

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The augmentation in electricity demand, power system privatization as well as efficacy of renewable resources has paved the way for power system companies and researchers to exploit the field of grid connected distributed generation (DG) and its issues, islanding being a dominant one. Several research works have been conducted to mitigate the issues of islanding detection (ID). In context of this, the paper gives a comprehensive review of islanding issues, standard test systems, criteria and shifting of research trends in islanding detection methods (IDMs). The significant contributions pertain to categorization of IDMs, evaluation of non-detection zone (NDZ) for each test system, disquisition on evolution and advancement of IDMs and its comparisons based on criteria such as NDZ, run on time, nuisance tripping percentage, applicability in multi DG system and implementation cost to draw out the strength and shortcomings of individual methods that will come to aid to the companies or researchers for establishing the applicability and appropriateness of such method for their concerned domain.

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“…Similarly, application of support vector machine for enhancement in the performance of passive islanding detection technqiue has been proposed in [36][37][38]. Apart from these, probabilistic neural network [39] and artificial neural network [40] are also utilized in the passive islanding detection techniques to enhance their performance.…”

Section: Passive Islanding Detection Techniquesmentioning

confidence: 99%

An islanding detection strategy for distribution network connected with hybrid DG resources

Laghari

Mokhlis

Karimi

et al. 2015

Renewable and Sustainable Energy Reviews

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Average rate of change of reactive power Bio-Mass Mini-hydro a b s t r a c tThe exponential growth in electricity demand has driven the Distributed Generation (DG) technology a boost in the power system. The use of DG is beneficial to power utilities, DG owners', and end-users in terms of reliability, power quality, and economics. However, to fully utilize the benefits of DGs, some technical issues need to be addressed. Islanding condition is one of the most important issue in this context. Until now, several islanding detection techniques have been proposed for detecting the islanding condition. This paper presents a brief overview of existing islanding detection techniques with their relative merits and demerits. Apart from this, the paper presents an islanding detection strategy suitable for hybrid DG resources of mini-hydro and Bio-Mass. The proposed strategy uses average rate of change of reactive power and load shift strategy to detect islanding of the distribution network. The performance of proposed strategy is validated on various islanding and non-islanding events. The results of proposed strategy are compared with other existing techniques in terms of fast islanding detection, and non-detection zone. The simulation results show that the proposed strategy is effective in detecting islanding phenomenon possesses fast detection and negligible non-detection zone region compared to existing islanding detection techniques.

show abstract

Islanding detection method for DFIG wind turbines using artificial neural networks

Cited by 48 publications

References 15 publications

Computational Intelligence based techniques for islanding detection of distributed generation in distribution network: A review

Computational Intelligence based techniques for islanding detection of distributed generation in distribution network: A review

Shifting of research trends in islanding detection method - a comprehensive survey

An islanding detection strategy for distribution network connected with hybrid DG resources

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