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IET Smart Grid - 2022 - Bayati - EMD HT‐based local fault detection in DC microgrid clusters.pdf (1.52 MB)

EMD/HT-based local fault detection in DC microgrid clusters

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posted on 2022-06-01, 11:06 authored by Navid Bayati, Hamid Reza Baghaee, Mehdi Savaghebi, Amin Hajizadeh, Mohsen Soltani, Zhengyu LinZhengyu Lin

DC faults can create serious damages if not detected and isolated in a short time. This paper proposes a fault detection technique for DC faults to enhance the protection of DC microgrid clusters. To detect such faults accurately and quickly, a DC fault detection scheme using empirical mode decomposition and Hilbert transform is proposed. Due to the strict time limits for fault interruption caused by fast high-rising fault currents in DC systems, DC microgrid clusters' protection remains a challenging task. Furthermore, high impedance faults (HIFs) in DC systems cause a small change in the current, which can damage the power electronic converters if not detected in time. Therefore, this paper proposes a local scheme for the fast detection of faults including HIFs in DC microgrid clusters. Both simulation and experimental results using a scaled DC microgrid cluster prototype and considering several scenarios (such as low impedance faults, HIFs, noise, overload, and bad calibration of sensors) demonstrate the successful and fast detection (less than 2 ms) of DC faults by the proposed method. Compared with other techniques, the proposed scheme presents its merits from the viewpoints of accuracy and speed.

History

School

  • Mechanical, Electrical and Manufacturing Engineering

Published in

IET Smart Grid

Volume

5

Issue

3

Pages

177 - 188

Publisher

John Wiley & Sons Ltd on behalf of The Institution of Engineering and Technology

Version

  • VoR (Version of Record)

Rights holder

© The Authors

Publisher statement

This is an Open Access Article. It is published by John Wiley & Sons Ltd on behalf of The Institution of Engineering and Technology under the Creative Commons Attribution-NonCommercial 4.0 International Licence (CC BY-NC). Full details of this licence are available at: https://creativecommons.org/licenses/by-nc/4.0/

Acceptance date

2022-02-12

Publication date

2022-02-24

Copyright date

2022

eISSN

2515-2947

Language

  • en

Depositor

Dr Zhengyu Lin . Deposit date: 14 February 2022

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