A complete fault location formulation for distribution systems using the k-nearest neighbors for regression and classification

G. Morales-España, J. Mora-Flórez, G. Carrillo-Caicedo

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

7 Citations (Scopus)

Abstract

This paper presents an alternative to the traditional impedance based fault location methods, using a simple technique of the learning approaches called k-Nearest Neighbors (k-NN), where besides the fault location distance, the multiple estimation problem is also addressed. This approach only uses the single end measurements of voltage and current available at the power substation.

Original languageEnglish
Title of host publication2010 IEEE/PES Transmission and Distribution Conference and Exposition: Latin America, T and D-LA 2010
PublisherIEEE
Pages810-815
Number of pages6
ISBN (Electronic)978-1-4577-0488-8
ISBN (Print)9781457704871
DOIs
Publication statusPublished - 2011
Externally publishedYes
Event2010 IEEE/PES Transmission and Distribution Conference and Exposition: Latin America, T and D-LA 2010 - Sao Paulo, Brazil
Duration: 8 Nov 201010 Nov 2010

Conference

Conference2010 IEEE/PES Transmission and Distribution Conference and Exposition: Latin America, T and D-LA 2010
CountryBrazil
CitySao Paulo
Period8/11/1010/11/10

Keywords

  • Classification
  • fault location
  • k-Nearest Neighbors
  • learning approaches
  • multiple estimation
  • power distribution systems
  • regression

Fingerprint Dive into the research topics of 'A complete fault location formulation for distribution systems using the k-nearest neighbors for regression and classification'. Together they form a unique fingerprint.

Cite this