Abstract
This paper presents a new composite approach based on wavelet-Transform and ANN for islanding detection of distributed generation (DG). The proposed method first uses wavelet-Transform to detect the occurrence of events, and then uses artificial neural network (ANN) to classify islanding and non-islanding events. Total harmonic distortion and voltage unbalance are extracted as feature inputs for ANN classifier. The performance of the proposed method is tested by simulations for two typical distribution networks based on MATLAB/Simulink. The results show that the developed method can effectively detect islanding with low misclassification. The method has the advantages of small non-detection zone and robustness against noises.
Original language | English |
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Article number | 20190074 |
Journal | International Journal of Emerging Electric Power Systems |
Volume | 20 |
Issue number | 5 |
DOIs | |
State | Published - Oct 1 2019 |
Bibliographical note
Publisher Copyright:© 2019 Walter de Gruyter GmbH, Berlin/Boston 2019.
Keywords
- artificial neural network
- islanding detection
- power system protection
ASJC Scopus subject areas
- Energy Engineering and Power Technology