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

Research output: Chapter in Book/Inform › Chapter › Research

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 language	English (US)
Title of host publication	Applications of Computational Intelligence - First IEEE Colombian Conference, ColCACI 2018, Medellín, Colombia, May 16–18, 2018, Revised Selected Papers
Editors	Alvaro David Orjuela-Cañón, Juan Carlos Figueroa-García, Julián David Arias-Londoño
Publisher	Springer
Pages	63-74
Number of pages	12
ISBN (Print)	9783030030223
DOIs	https://doi.org/10.1007/978-3-030-03023-0_6
State	Published - 2018
Externally published	Yes
Event	1st IEEE Colombian Conference on Applications in Computational Intelligence, ColCACI 2018 - Medellin, Colombia Duration: May 16 2018 → May 18 2018

Publication series

Name	Communications in Computer and Information Science
Volume	833
ISSN (Print)	1865-0929

Conference

Conference	1st IEEE Colombian Conference on Applications in Computational Intelligence, ColCACI 2018
Country/Territory	Colombia
City	Medellin
Period	5/16/18 → 5/18/18

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 7 Affordable and Clean Energy

All Science Journal Classification (ASJC) codes

General Computer Science
General Mathematics

Access to Document

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

Cite this

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. In 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).

@inbook{8ba4e0a647ab4d64809253e44061f355,

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",

language = "English (US)",

isbn = "9783030030223",

series = "Communications in Computer and Information Science",

publisher = "Springer",

pages = "63--74",

editor = "Orjuela-Ca{\~n}{\'o}n, \{Alvaro David\} and Figueroa-Garc{\'i}a, \{Juan Carlos\} and Arias-Londo{\~n}o, \{Juli{\'a}n David\}",

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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. in 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).

Research output: Chapter in Book/Inform › Chapter › Research

TY - CHAP

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.

UR - https://www.scopus.com/pages/publications/85058998061

UR - https://www.scopus.com/pages/publications/85058998061#tab=citedBy

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M3 - Chapter

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SN - 9783030030223

T3 - Communications in Computer and Information Science

SP - 63

EP - 74

BT - Applications of Computational Intelligence - First IEEE Colombian Conference, ColCACI 2018, Medellín, Colombia, May 16–18, 2018, Revised Selected Papers

A2 - Orjuela-Cañón, Alvaro David

A2 - Figueroa-García, Juan Carlos

A2 - Arias-Londoño, Julián David

PB - Springer

T2 - 1st IEEE Colombian Conference on Applications in Computational Intelligence, ColCACI 2018

Y2 - 16 May 2018 through 18 May 2018

ER -

de Dios Fuentes Velandia J, Orjuela-Cañón AD, Tangarife Escobar HI. Discrimination of nonlinear loads in electric energy generation systems using harmonic information. In Orjuela-Cañón AD, Figueroa-García JC, Arias-Londoño JD, editors, 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

Abstract

Publication series

Conference

UN SDGs

All Science Journal Classification (ASJC) codes

Access to Document

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