Variational mode decomposition
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            subspace‐K‐nearest neighbour based islanding detection in distributed generation system

Patnaik, Bhaskar; Mishra, Manohar; Jena, Ranjan Kumar

doi:10.1002/2050-7038.12900

Cited by 7 publications

(3 citation statements)

References 43 publications

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“…In [163] is proposed a new Negative-Sequence based AIP that inserts positive-feedback disturbance given by (34).…”

Section: ) Negative-sequence Current Injectionmentioning

confidence: 99%

“…The results indicate islanding capabilities for load with 3.5 f Q  even in a 20dB signal to noise rate. In [34], is proposed approach utilizes VMD and Subspace-K-Nearest Neighbor (SSKNN) method to detect islanding events. The proposed method extracts 3-phase voltage signals, applies VMD to obtain principal modes, and formulates four feature indices based on the first three modes.…”

Section: ) Variational Mode Decomposition (Vmd)mentioning

confidence: 99%

“…These methods, however, depend on a high computational burden and on an elevated number of sensors depending on how much are the inputs of the algorithm. Finally, there is another set of AIP methodologies based on passive detection that use signal processing methods to improve durability, reliability, and effectiveness, namely: Fourier Transform (FT) [29], Wavelet Transform (WT) [30], Stockwel Transform (ST) [31], Mathematical Morphology (MM) [32], Kalman Filter (KF) [33], Variation Mode Decomposition (VMD) [34] and Empirical Mode Decomposition (EMD) [35].…”

Section: Introductionmentioning

confidence: 99%

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Anti-Islanding Techniques for Integration of Inverter-Based Distributed Energy Resources to the Electric Power System

Resende,

Simões,

Freitas

2024

IEEE Access

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The emergence of microgrids and the increasing adoption of Distributed Generation Systems (DGS) have created an opportunity to replace traditional fossil fuels with renewable resources. Such a shift poses security and power quality challenges that must be addressed by academics and industrial research paradigms. Unintentional islanding is an important security concern, as it can result in power quality degradation, electrical hazards, and equipment damage. To address this problem and find efficient solutions, many anti-islanding techniques to detect and eliminate the phenomenon can be found in the specialized literature. These solutions can be classified as passive, active, remote, hybrid, or based on machine learning and signal processing techniques. In this context, this paper provides a comprehensive review of existing antiislanding methods, highlighting their importance in preventing dangerous situations. The review includes a detailed analysis of advantages and limitations found for each method, as well as its suitability for practical applications. The goal is to provide a valuable resource for researchers and practitioners in the field of distributed power systems, enabling them to choose the most appropriate anti-islanding method for their specific needs. Overall, this paper aims to address the challenges posed by unintentional islanding and promote the adoption of renewable energy resources for a more sustainable future.

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“…In [163] is proposed a new Negative-Sequence based AIP that inserts positive-feedback disturbance given by (34).…”

Section: ) Negative-sequence Current Injectionmentioning

confidence: 99%

Section: ) Variational Mode Decomposition (Vmd)mentioning

confidence: 99%