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Fault detection and classification of DC microgrid based on VMD

Subrat Kumar Barik (School of Electrical Engineering, KIIT University, Bhubaneswar, India)

COMPEL - The international journal for computation and mathematics in electrical and electronic engineering

ISSN: 0332-1649

Article publication date: 7 June 2022

Issue publication date: 20 January 2023

234

Abstract

Purpose

This paper aims to present a new fault detection and classification scheme of both DC faults and AC faults on a DC microgrid network.

Design/methodology/approach

To achieve reliable protection, the derivative of DC current signal is decomposed into several intrinsic modes using variational mode decomposition (VMD), which are then used as inputs to the Hilbert–Haung transform technique to obtain the instantaneous amplitude and frequency of the decomposed modes of the signal. A weighted Kurtosis index is used to obtain the most sensitive mode, which is used to compute sudden change in discrete Teager energy (DTE), indicating the occurrence of the fault. A stacked autoencoder-based neural network is applied for classifying the pole to ground (PG), pole to pole (PP), line to ground (LG), line to line (LL) and three-phase line to ground (LLLG) faults. The effectiveness of the proposed protection technique is validated in MATLAB/SIMULINK by considering different test cases.

Findings

As the maximum fault detection time is only 5 ms, the proposed detection technique is very fast. A stacked autoencoder-based neural network is applied for classifying the PG, PP, LG, LL and LLLG faults with classification accuracy of 99.1%.

Originality/value

The proposed technique provides a very fast, reliable and accurate protection scheme for DC microgrid system.

Keywords

Citation

Barik, S.K. (2023), "Fault detection and classification of DC microgrid based on VMD", COMPEL - The international journal for computation and mathematics in electrical and electronic engineering, Vol. 42 No. 2, pp. 302-322. https://doi.org/10.1108/COMPEL-09-2021-0358

Publisher

:

Emerald Publishing Limited

Copyright © 2022, Emerald Publishing Limited

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