Download PDFOpen PDF in browser
PT
Switch back to the title and the abstract
in Portuguese

Fault Location in Radial Distribution Systems Based on Empirical Mode Decomposition: an Analysis of the Effects of Sampling Frequency

EasyChair Preprint 11120

8 pagesDate: October 23, 2023

Abstract

In recent years, the electrical system has undergone numerous transformations with the emergence of new load profiles, expansion of distributed generation, and the distribution system. In conjunction, regulatory standards have been enhanced to ensure the continuity and reliability of electricity supply. Fault localization is of paramount importance, as it is directly related to the time required to restore the electricity supply.
This article proposes an approach for fault localization in distribution systems based on high-frequency signal analysis, using the Empirical Mode Decomposition (EMD) method to detect, following a fault occurrence, the time instances of waves reflected at the line ends. The proposed approach was validated through simulations in PSCAD/EMTP software, considering the CIGRE test system with radial topology and adapted for 60 Hz. The results were analyzed for different sampling frequency values, considering their effects on the proposed methodology. The results proved satisfactory for sampling frequencies between 12 MHz and 4 MHz, with an average error ranging from 0.6% to 2.3% (with a standard deviation of 0.31% to 2.5%) in fault distance estimation.

Keyphrases: Alimentadores Radiais, Decomposição de Modo Empírico, Localização de Faltas, Ondas Viajantes, Sistema de Distribuição

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
@booklet{EasyChair:11120,
  author    = {Leonardo Lessa and Caio Grilo and Denis Coury and Ricardo Fernandes},
  title     = {Fault Location in Radial Distribution Systems Based on Empirical Mode Decomposition: an Analysis of the Effects of Sampling Frequency},
  howpublished = {EasyChair Preprint 11120},
  year      = {EasyChair, 2023}}
Download PDFOpen PDF in browser