Wang, N., Aravinthan, V. and Ding, Y. (2014) Feeder-Level Fault Detection and Classification with Multiple Sensors: A Smart Grid Scenario. 2014 IEEE Workshop on Statistical Signal Processing (SSP), Gold Coast, 29 June-2 July 2014, 37-40.
https://doi.org/10.1109/SSP.2014.6884569

has been cited by the following article:

• TITLE: Review of Fault Types, Impacts, and Management Solutions in Smart Grid Systems

  AUTHORS: Mohammed Mousa, Sherif Abdelwahed, Joni Kluss

  KEYWORDS: Detecting Fault, Fault Management, Impact of Renewable Energy Resources, Isolating Faulty Load, Locating Fault, Matlab/Simulink, RTDS, Smart Grid System, Types of Faults

  JOURNAL NAME: Smart Grid and Renewable Energy, Vol.10 No.4, April 30, 2019

  ABSTRACT: Fault management study in smart grid systems (SGSs) is important to ensure the stability of the system. Also, it is important to know the major types of power failures for the effective operation of the SGS. This paper reviews diverse types of faults that might appear in the SGS and gives a survey about the impact of renewable energy resources (RERs) on the behavior of the system. Moreover, this paper offers different fault detection and localization techniques that can be used for SGSs. Furthermore, a potential fault management case study is proposed in this paper. The SGS model in this paper is investigated using both of the Matlab/Simulink and the Real Time Digital Simulation (RTDS) to compute the fault management study. Simulation results show the fast response to a power failure in the system which improves the stability of the SGS.