Faults in smart grid systems: Monitoring, detection and classification

•A systematic review for Smart Grid systems faults.•A classification framework on relevant grid requirements.•Future developments related to fault detection and classification.•Advance Metering Infrastructure under the perspective of power faults. Smart Grid (SG) is a multidisciplinary concept relat...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Electric power systems research 2020-12, Vol.189 (C), p.106602, Article 106602
Hauptverfasser: Labrador Rivas, Angel Esteban, Abrão, Taufik
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:•A systematic review for Smart Grid systems faults.•A classification framework on relevant grid requirements.•Future developments related to fault detection and classification.•Advance Metering Infrastructure under the perspective of power faults. Smart Grid (SG) is a multidisciplinary concept related to the power system update and improvement. SG implies real-time information with specific communication requirements. System reliability relies on the best capabilities for monitoring and controlling the grid. Among other aspects, SG applications involve three main challenges, sufficient real-time capable measurement units, managing large data sets, and two-way low-latency communications. Considering fault detection and classification a key factor to SG reliability, this work provides a systematic review of SG faults from the most significant research databases and state-of-the-art research papers aiming at creating a comprehensive classification framework on the relevant requirements. This paper includes in detail the classification of different fault scenarios in a comprehensive framework that involves system-level of application, e.g., transmission, distribution, commercial, DG, and EV. To this end, We analyze and indicate relevant topics for future developments related to the monitoring and fault detection and classification in SG systems.
ISSN:0378-7796
1873-2046
DOI:10.1016/j.epsr.2020.106602