Discrimination of nonlinear loads in electric energy generation systems using harmonic information

Juan de Dios Fuentes Velandia, Alvaro David Orjuela-Cañón, Héctor Iván Tangarife Escobar

Research output: Chapter in Book/ReportConference contribution

Abstract

This paper contains a proposal to determine the kind of nonlinear load when are connected to the solar or conventional generation system. A database was built with sampled signals extracted from the photovoltaic system of the National Learning Service (SENA) in Bogota, Colombia. The used methodology has an acquisition system of voltage signals, and then, information from harmonic distortion was employed to identify the nonlinear loads. An artificial neural network was implemented to discriminate appliances with supervised learning. Two proposals were implemented. First one was based on energy information and second one was worked with wave peaks information. Results show that a classification rate of 95% could be reached in a problem with eight classes.

Original languageEnglish (US)
Title of host publicationApplications of Computational Intelligence - First IEEE Colombian Conference, ColCACI 2018, Medellín, Colombia, May 16–18, 2018, Revised Selected Papers
EditorsAlvaro David Orjuela-Cañón, Juan Carlos Figueroa-García, Julián David Arias-Londoño
PublisherSpringer
Pages63-74
Number of pages12
ISBN (Print)9783030030223
DOIs
StatePublished - 2018
Externally publishedYes
Event1st IEEE Colombian Conference on Applications in Computational Intelligence, ColCACI 2018 - Medellin, Colombia
Duration: May 16 2018May 18 2018

Publication series

NameCommunications in Computer and Information Science
Volume833
ISSN (Print)1865-0929

Conference

Conference1st IEEE Colombian Conference on Applications in Computational Intelligence, ColCACI 2018
Country/TerritoryColombia
CityMedellin
Period5/16/185/18/18

All Science Journal Classification (ASJC) codes

  • General Computer Science
  • General Mathematics

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