A Novel Passive Islanding Detection Methods Using Wavelet Transform for Grid Connected PV System

Koduri, Omkar; Duvvuri, Sssr Sarathbabu; Varma, Sagiraju Dileep Kumar

doi:10.1109/iciinfs.2018.8721382

Cited by 5 publications

(1 citation statement)

References 9 publications

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“…It is the passive method form with the capability for hidden feature extraction of any signal, which is an added advantage. Commonly used SP methods are Fourier transform [32], Stockwell transform [33], wavelet transform [34], Hilbert-Huang transform [35], matrix pencil method [36], etc. Although the accuracy of islanding operation detection is improved by the SP approaches, the detection based on the extraction signal feature can be hard in more complicated network structures.…”

Section: Idm Methods Classificationmentioning

confidence: 99%

Application of Artificial Neural Networks to Islanding Detection in Distribution Grids: A Literature Review

Kaluđer,

Fekete,

Čvek

et al. 2023

Applied Sciences

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Active distribution grids that contain energy sources (so-called distributed generation or DG) are nowadays a reality. Besides the many benefits DGs bring to the distribution grid, some challenges are associated with their integration. Since there are DGs now in the distribution grid, the occurrence of islanding operation is possible. Since an islanding operation can be dangerous, it is necessary to have an effective method to detect it. In the last decade, scientists have made a great effort to develop and test various islanding detection methods (IDMs). Many approaches have been tested, and the methods based on computational intelligence (CI) have shown great potential. Among them, artificial neural networks (ANNs) gained most of the research attention. This paper focuses on ANN application for islanding detection. It gives an exhaustive review of the ANN types used for islanding detection, the types of input data, and their transformation to fit the ANNs. Furthermore, various applications based on specific input data, preprocessing types, different learning algorithms, real-time implementation, and various distribution models used for ANN are reviewed. This paper investigates the potential of ANNs to enhance islanding detection accuracy, reduce non-detection zone (NDZ), and contribute to an overall efficient detection method.

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