A robust wavelet-ANN based technique for islanding detection

Mohamed S. ElNozahy, Ehab F. El-Saadany, Magdy M.A. Salama

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

54 Scopus citations

Abstract

A simple and robust approach for islanding detection is introduced in this paper. The proposed approach detects islanding using the transient signals. The three phases' currents seen at the DG terminals are combined into one modal signal that fully represents the system. The feature vector is extracted from the selected modal current signal utilizing discrete wavelet transform. The extracted feature vector is then used to train an artificial neural network to detect islanding. Based on the training results the proposed approach was modified to obtain the characteristic signature that characterizes islanding events thus the computational burden is reduced to minimum. Tests were conducted on the proposed algorithm to validate its robustness. Test results showed that the algorithm is reliable and fast.

Original languageBritish English
Title of host publication2011 IEEE PES General Meeting
Subtitle of host publicationThe Electrification of Transportation and the Grid of the Future
DOIs
StatePublished - 2011
Event2011 IEEE PES General Meeting: The Electrification of Transportation and the Grid of the Future - Detroit, MI, United States
Duration: 24 Jul 201128 Jul 2011

Publication series

NameIEEE Power and Energy Society General Meeting
ISSN (Print)1944-9925
ISSN (Electronic)1944-9933

Conference

Conference2011 IEEE PES General Meeting: The Electrification of Transportation and the Grid of the Future
Country/TerritoryUnited States
CityDetroit, MI
Period24/07/1128/07/11

Keywords

  • Artificial neural network
  • characteristic signature
  • discrete wavelet transform
  • energy spectrum
  • Islanding detection

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