Fault Detection in DC Microgrids Using Short-Time
The most common faults in DC microgrids are pole-to-pole (PP), pole-to-ground (PG), and two PG (2PG) faults. Pole-to-pole faults appear to a smaller extent, but can cause extremely high currents and damage to the
Fault Detection in DC Microgrids using Recurrent Neural Networks
Reliable and accurate fault detection plays a crucial role in the microgrid operation by enabling an increased operational flexibility. Successful classification of events in complex microgrid
Higher Order Sliding Mode Observer-Based Sensor Fault Detection in DC
Fault detection in a Direct Current (DC) microgrid with multiple interconnections of distributed generation units (DGUs) is an interesting topic of research. The occurrence of
Unknown Input Observer-Based Series DC Arc Fault Detection in
In this article, a fault detection and isolation technique for series arc faults in dc microgrids with multiple power electronics loads is proposed using unknown input observers
High‐speed algorithm for fault detection and location
The proposed protection algorithm detects and locates DC faults with high resistances, utilizing fault detection and location, employing the high-order synchrosqueezing transform that determines magn Abstract
Fault Detection in DC Microgrids Using Short-Time
The paper proposes a fast fault detection method for radial DC microgrids established on mathematical morphology (MM) denoising filters and detection principles utilizing only local measurements.
DC microgrid fault detection using multiresolution analysis of
Importance of fast detection of faults in a DC microgrid to increase the lifetime of power electronics switches and enhance the controllability over converters. [17], cable
Fault detection and synchronization control in hybrid DC/AC
This paper introduces a DC-link fault detection and synchronization control strategy for grid-forming inverters in hybrid DC/AC microgrids, aiming to bolster system stability and reliability.
High‐speed algorithm for fault detection and location in DC microgrids
The proposed protection algorithm detects and locates DC faults with high resistances, utilizing fault detection and location, employing the high-order synchrosqueezing
LPV Model-Based Fault Detection and Isolation in DC Microgrids
The safety of DC microgrids is threatened by multiple types of faults occurring in different components, entailing multi-target fault detection and isolation solutions. To address this
Model-Based Fault Detection and Isolation in DC Microgrids Using
DC microgrids require advanced protection techniques for fault detection and isolation (FDI). In this work, an FDI method able to respond to different types of component faults is developed
Learning approach based DC arc fault location classification in DC
The series DC arc fault can happen at arbitrary locations of any DC systems with a high voltage DC bus [16], [17], [18].Hence, a comprehensive investigation of DC arc fault in
Fault detection and synchronization control in hybrid DC/AC microgrids
This paper introduces a DC-link fault detection and synchronization control strategy for grid-forming inverters in hybrid DC/AC microgrids, aiming to bolster system stability and reliability.
6 FAQs about [Fault Detection in DC Microgrids]
Do DC microgrids require advanced protection techniques for fault detection and isolation?
Abstract: DC microgrids require advanced protection techniques for fault detection and isolation (FDI). In this work, an FDI method able to respond to different types of component faults is developed based on system modeling. First, the state-space representation of a multiterminal dc microgrid with component faults is derived.
How to detect faults in DC microgrids?
In , cable current derivatives are utilized to detect faults in DC microgrids. Alternatively, traveling wave (TW) protection schemes have been introduced to accommodate a faster tripping protection in electric power grids. These schemes rely on high-frequency measurements.
Can Gaussian process detect faults in a simple dc microgrid?
In , Gaussian Process (GP) is used to detect faults in a simple DC system. In this paper, a TW protection scheme utilizing machine learning (ML) for DC microgrids is proposed. The proposed scheme utilizes discrete wavelet transform (DWT) to calculate the high-frequency components of DC fault currents.
How effective is FDI method for detecting faults in DC microgrids?
The performance of the proposed FDI method is verified under the real-time (RT) simulation of a three-terminal low-voltage dc microgrid and with a small-scale laboratory dc grid. The proposed FDI method is proved to be effective to detect and isolate different faults in dc microgrids with a response time of 1 ms.
Why is data-driven fault detection a major constraint for DC microgrids?
Good robustness against measurement noises and changes in system configurations. The lack of fault data is the major constraint on data-driven fault detection and isolation schemes for DC microgrids.
Why is a dc microgrid important?
No zero crossing of current in DC systems makes the interruption of fault currents with fuses and circuit breakers more difficult which in turn creates arcing and long fault clearing time . On the other hand, fast detection and isolation of faults in a DC microgrid is of particular importance , , .