Nonlinear loads determination using harmonic information in photovoltaic generation systems

Juan De DIos Fuentes, Alvaro D. Orjuela-Cañón, Héctor Iván Tangarife Escobar

Research output: Contribution to conferenceConference proceedingspeer-review

1 Scopus citations

Abstract

This paper contains a proposal to determine the kind of nonlinear load when different appliances are connected to the solar generation system. A database built with sampled signals from the photovoltaic systems of the National Learning Service (SENA) in Bogota was employed. The methodology used information from harmonic distortion extracted from nonlinear loads, which was used as input in an artificial neural network 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)
DOIs
StatePublished - Oct 5 2018
Externally publishedYes
Event1st IEEE Colombian Conference on Applications in Computational Intelligence, ColCACI 2018 - Medellin, Colombia
Duration: May 16 2018May 18 2018

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

  • Artificial Intelligence
  • Computer Science Applications

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