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

Producción científica: Capítulo en Libro/ReporteContribución a la conferencia

Resumen

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.

Idioma originalInglés estadounidense
Título de la publicación alojadaApplications of Computational Intelligence - First IEEE Colombian Conference, ColCACI 2018, Medellín, Colombia, May 16–18, 2018, Revised Selected Papers
EditoresAlvaro David Orjuela-Cañón, Juan Carlos Figueroa-García, Julián David Arias-Londoño
EditorialSpringer
Páginas63-74
Número de páginas12
ISBN (versión impresa)9783030030223
DOI
EstadoPublicada - 2018
Publicado de forma externa
Evento1st IEEE Colombian Conference on Applications in Computational Intelligence, ColCACI 2018 - Medellin, Colombia
Duración: may. 16 2018may. 18 2018

Serie de la publicación

NombreCommunications in Computer and Information Science
Volumen833
ISSN (versión impresa)1865-0929

Conferencia

Conferencia1st IEEE Colombian Conference on Applications in Computational Intelligence, ColCACI 2018
País/TerritorioColombia
CiudadMedellin
Período5/16/185/18/18

Áreas temáticas de ASJC Scopus

  • Ciencia de la Computación General
  • Matemáticas General

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