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

Allan Manito, Ubiratan Bezerra, Maria Tostes, Edson Matos, Carminda Carvalho and Thiago Soares
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Allan Manito: Electrical Engineering Faculty, Institute of Technology, Federal University of Pará, Belém PA 66075-110, Brazil
Ubiratan Bezerra: Electrical Engineering Faculty, Institute of Technology, Federal University of Pará, Belém PA 66075-110, Brazil
Maria Tostes: Electrical Engineering Faculty, Institute of Technology, Federal University of Pará, Belém PA 66075-110, Brazil
Edson Matos: Electrical Engineering Faculty, Institute of Technology, Federal University of Pará, Belém PA 66075-110, Brazil
Carminda Carvalho: Electrical Engineering Faculty, Institute of Technology, Federal University of Pará, Belém PA 66075-110, Brazil
Thiago Soares: Electrical Engineering Faculty, Institute of Technology, Federal University of Pará, Belém PA 66075-110, Brazil

Energies, 2018, vol. 11, issue 12, 1-13

Abstract: 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.

Keywords: artificial neural network; harmonic current; harmonic voltage; alternative transient program; harmonic distortion contribution (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2018
References: View complete reference list from CitEc
Citations: View citations in EconPapers (4)

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