Evaluating Harmonic Distortions on Grid Voltages Due to Multiple Nonlinear Loads Using Artificial Neural Networks

This paper presents a procedure to estimate the impacts on voltage harmonic distortion at a point of interest due to multiple nonlinear loads in the electrical network. Despite artificial neural networks (ANN) being a widely used technique for the solution of a large amount and variety of issues in...

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Main Authors: Allan Manito, Ubiratan Bezerra, Maria Tostes, Edson Matos, Carminda Carvalho, Thiago Soares
Format: Article
Language:English
Published: MDPI AG 2018-11-01
Series:Energies
Subjects:
Online Access:https://www.mdpi.com/1996-1073/11/12/3303
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spelling doaj-7a537656a50840dfa5a4267c9e3784512020-11-24T23:31:41ZengMDPI AGEnergies1996-10732018-11-011112330310.3390/en11123303en11123303Evaluating Harmonic Distortions on Grid Voltages Due to Multiple Nonlinear Loads Using Artificial Neural NetworksAllan Manito0Ubiratan Bezerra1Maria Tostes2Edson Matos3Carminda Carvalho4Thiago Soares5Electrical Engineering Faculty, Institute of Technology, Federal University of Pará, Belém PA 66075-110, BrazilElectrical Engineering Faculty, Institute of Technology, Federal University of Pará, Belém PA 66075-110, BrazilElectrical Engineering Faculty, Institute of Technology, Federal University of Pará, Belém PA 66075-110, BrazilElectrical Engineering Faculty, Institute of Technology, Federal University of Pará, Belém PA 66075-110, BrazilElectrical Engineering Faculty, Institute of Technology, Federal University of Pará, Belém PA 66075-110, BrazilElectrical Engineering Faculty, Institute of Technology, Federal University of Pará, Belém PA 66075-110, BrazilThis paper presents a procedure to estimate the impacts on voltage harmonic distortion at a point of interest due to multiple nonlinear loads in the electrical network. Despite artificial neural networks (ANN) being a widely used technique for the solution of a large amount and variety of issues in electric power systems, including harmonics modeling, its utilization to establish relationships among the harmonic voltage at a point of interest in the electric grid and the corresponding harmonic currents generated by nonlinear loads was not found in the literature, thus this innovative procedure is considered in this article. A simultaneous measurement campaign must be carried out in all nonlinear loads and at the point of interest for data acquisition to train and test the ANN model. A sensitivity analysis is proposed to establish the percent contribution of load currents on the observed voltage distortion, which constitutes an original definition presented in this paper. Initially, alternative transient program (ATP) simulations are used to calculate harmonic voltages at points of interest in an industrial test system due to nonlinear loads whose harmonic currents are known. The resulting impacts on voltage harmonic distortions obtained by the ATP simulations are taken as reference values to compare with those obtained by using the proposed procedure based on ANN. By comparing ATP results with those obtained by the ANN model, it is observed that the proposed methodology is able to classify correctly the impact degree of nonlinear load currents on voltage harmonic distortions at points of interest, as proposed in this paper.https://www.mdpi.com/1996-1073/11/12/3303artificial neural networkharmonic currentharmonic voltagealternative transient programharmonic distortion contribution
collection DOAJ
language English
format Article
sources DOAJ
author Allan Manito
Ubiratan Bezerra
Maria Tostes
Edson Matos
Carminda Carvalho
Thiago Soares
spellingShingle Allan Manito
Ubiratan Bezerra
Maria Tostes
Edson Matos
Carminda Carvalho
Thiago Soares
Evaluating Harmonic Distortions on Grid Voltages Due to Multiple Nonlinear Loads Using Artificial Neural Networks
Energies
artificial neural network
harmonic current
harmonic voltage
alternative transient program
harmonic distortion contribution
author_facet Allan Manito
Ubiratan Bezerra
Maria Tostes
Edson Matos
Carminda Carvalho
Thiago Soares
author_sort Allan Manito
title Evaluating Harmonic Distortions on Grid Voltages Due to Multiple Nonlinear Loads Using Artificial Neural Networks
title_short Evaluating Harmonic Distortions on Grid Voltages Due to Multiple Nonlinear Loads Using Artificial Neural Networks
title_full Evaluating Harmonic Distortions on Grid Voltages Due to Multiple Nonlinear Loads Using Artificial Neural Networks
title_fullStr Evaluating Harmonic Distortions on Grid Voltages Due to Multiple Nonlinear Loads Using Artificial Neural Networks
title_full_unstemmed Evaluating Harmonic Distortions on Grid Voltages Due to Multiple Nonlinear Loads Using Artificial Neural Networks
title_sort evaluating harmonic distortions on grid voltages due to multiple nonlinear loads using artificial neural networks
publisher MDPI AG
series Energies
issn 1996-1073
publishDate 2018-11-01
description This paper presents a procedure to estimate the impacts on voltage harmonic distortion at a point of interest due to multiple nonlinear loads in the electrical network. Despite artificial neural networks (ANN) being a widely used technique for the solution of a large amount and variety of issues in electric power systems, including harmonics modeling, its utilization to establish relationships among the harmonic voltage at a point of interest in the electric grid and the corresponding harmonic currents generated by nonlinear loads was not found in the literature, thus this innovative procedure is considered in this article. A simultaneous measurement campaign must be carried out in all nonlinear loads and at the point of interest for data acquisition to train and test the ANN model. A sensitivity analysis is proposed to establish the percent contribution of load currents on the observed voltage distortion, which constitutes an original definition presented in this paper. Initially, alternative transient program (ATP) simulations are used to calculate harmonic voltages at points of interest in an industrial test system due to nonlinear loads whose harmonic currents are known. The resulting impacts on voltage harmonic distortions obtained by the ATP simulations are taken as reference values to compare with those obtained by using the proposed procedure based on ANN. By comparing ATP results with those obtained by the ANN model, it is observed that the proposed methodology is able to classify correctly the impact degree of nonlinear load currents on voltage harmonic distortions at points of interest, as proposed in this paper.
topic artificial neural network
harmonic current
harmonic voltage
alternative transient program
harmonic distortion contribution
url https://www.mdpi.com/1996-1073/11/12/3303
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