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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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 |
work_keys_str_mv |
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