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

doi:10.1007/978-3-030-03023-0_6

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/Informe › Capítulo › Investigación

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 original	Inglés estadounidense
Título de la publicación alojada	Applications of Computational Intelligence - First IEEE Colombian Conference, ColCACI 2018, Medellín, Colombia, May 16–18, 2018, Revised Selected Papers
Editores	Alvaro David Orjuela-Cañón, Juan Carlos Figueroa-García, Julián David Arias-Londoño
Editorial	Springer
Páginas	63-74
Número de páginas	12
ISBN (versión impresa)	9783030030223
DOI	https://doi.org/10.1007/978-3-030-03023-0_6
Estado	Publicada - 2018
Publicado de forma externa	Sí
Evento	1st IEEE Colombian Conference on Applications in Computational Intelligence, ColCACI 2018 - Medellin, Colombia Duración: may. 16 2018 → may. 18 2018

Serie de la publicación

Nombre	Communications in Computer and Information Science
Volumen	833
ISSN (versión impresa)	1865-0929

Conferencia

Conferencia	1st IEEE Colombian Conference on Applications in Computational Intelligence, ColCACI 2018
País/Territorio	Colombia
Ciudad	Medellin
Período	5/16/18 → 5/18/18

Áreas temáticas de ASJC Scopus

Ciencia de la Computación General
Matemáticas General

ODS de las Naciones Unidas

Este resultado contribuye a los siguientes Objetivos de Desarrollo Sostenible

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10.1007/978-3-030-03023-0_6

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de Dios Fuentes Velandia, J., Orjuela-Cañón, A. D., & Tangarife Escobar, H. I. (2018). Discrimination of nonlinear loads in electric energy generation systems using harmonic information. En A. D. Orjuela-Cañón, J. C. Figueroa-García, & J. D. Arias-Londoño (Eds.), Applications of Computational Intelligence - First IEEE Colombian Conference, ColCACI 2018, Medellín, Colombia, May 16–18, 2018, Revised Selected Papers (pp. 63-74). (Communications in Computer and Information Science; Vol. 833). Springer. https://doi.org/10.1007/978-3-030-03023-0_6

de Dios Fuentes Velandia, Juan ; Orjuela-Cañón, Alvaro David ; Tangarife Escobar, Héctor Iván. / Discrimination of nonlinear loads in electric energy generation systems using harmonic information. Applications of Computational Intelligence - First IEEE Colombian Conference, ColCACI 2018, Medellín, Colombia, May 16–18, 2018, Revised Selected Papers. editor / Alvaro David Orjuela-Cañón ; Juan Carlos Figueroa-García ; Julián David Arias-Londoño. Springer, 2018. pp. 63-74 (Communications in Computer and Information Science).

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title = "Discrimination of nonlinear loads in electric energy generation systems using harmonic information",

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.",

author = "{de Dios Fuentes Velandia}, Juan and Orjuela-Ca{\~n}{\'o}n, {Alvaro David} and {Tangarife Escobar}, {H{\'e}ctor Iv{\'a}n}",

note = "Publisher Copyright: {\textcopyright} Springer Nature Switzerland AG 2018.; 1st IEEE Colombian Conference on Applications in Computational Intelligence, ColCACI 2018 ; Conference date: 16-05-2018 Through 18-05-2018",

year = "2018",

doi = "10.1007/978-3-030-03023-0_6",

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de Dios Fuentes Velandia, J, Orjuela-Cañón, AD & Tangarife Escobar, HI 2018, Discrimination of nonlinear loads in electric energy generation systems using harmonic information. En AD Orjuela-Cañón, JC Figueroa-García & JD Arias-Londoño (eds.), Applications of Computational Intelligence - First IEEE Colombian Conference, ColCACI 2018, Medellín, Colombia, May 16–18, 2018, Revised Selected Papers. Communications in Computer and Information Science, vol. 833, Springer, pp. 63-74, 1st IEEE Colombian Conference on Applications in Computational Intelligence, ColCACI 2018, Medellin, Colombia, 5/16/18. https://doi.org/10.1007/978-3-030-03023-0_6

Discrimination of nonlinear loads in electric energy generation systems using harmonic information. / de Dios Fuentes Velandia, Juan; Orjuela-Cañón, Alvaro David; Tangarife Escobar, Héctor Iván.
Applications of Computational Intelligence - First IEEE Colombian Conference, ColCACI 2018, Medellín, Colombia, May 16–18, 2018, Revised Selected Papers. ed. / Alvaro David Orjuela-Cañón; Juan Carlos Figueroa-García; Julián David Arias-Londoño. Springer, 2018. p. 63-74 (Communications in Computer and Information Science; Vol. 833).

Producción científica: Capítulo en Libro/Informe › Capítulo › Investigación

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T1 - Discrimination of nonlinear loads in electric energy generation systems using harmonic information

AU - de Dios Fuentes Velandia, Juan

AU - Orjuela-Cañón, Alvaro David

AU - Tangarife Escobar, Héctor Iván

N1 - Publisher Copyright: © Springer Nature Switzerland AG 2018.

PY - 2018

Y1 - 2018

N2 - 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.

AB - 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.

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de Dios Fuentes Velandia J, Orjuela-Cañón AD, Tangarife Escobar HI. Discrimination of nonlinear loads in electric energy generation systems using harmonic information. En Orjuela-Cañón AD, Figueroa-García JC, Arias-Londoño JD, editores, Applications of Computational Intelligence - First IEEE Colombian Conference, ColCACI 2018, Medellín, Colombia, May 16–18, 2018, Revised Selected Papers. Springer. 2018. p. 63-74. (Communications in Computer and Information Science). doi: 10.1007/978-3-030-03023-0_6

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

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