Academic Journal
Harmonic Distortion Prediction Model of a Grid-Tie Photovoltaic Inverter Using an Artificial Neural Network.
| Title: | Harmonic Distortion Prediction Model of a Grid-Tie Photovoltaic Inverter Using an Artificial Neural Network. |
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| Authors: | Žnidarec, Matej, Klaić, Zvonimir, Šljivac, Damir, Dumnić, Boris |
| Source: | Energies (19961073); Mar2019, Vol. 12 Issue 5, p790, 1p, 1 Color Photograph, 3 Diagrams, 7 Charts, 13 Graphs |
| Abstract: | Expanding the number of photovoltaic (PV) systems integrated into a grid raises many concerns regarding protection, system safety, and power quality. In order to monitor the effects of the current harmonics generated by PV systems, this paper presents long-term current harmonic distortion prediction models. The proposed models use a multilayer perceptron neural network, a type of artificial neural network (ANN), with input parameters that are easy to measure in order to predict current harmonics. The models were trained with one-year worth of measurements of power quality at the point of common coupling of the PV system with the distribution network and the meteorological parameters measured at the test site. A total of six different models were developed, tested, and validated regarding a number of hidden layers and input parameters. The results show that the model with three input parameters and two hidden layers generates the best prediction performance. [ABSTRACT FROM AUTHOR] |
| Subject Terms: | HARMONIC distortion (Physics), ELECTRIC power distribution grids, PHOTOVOLTAIC power systems, ARTIFICIAL neural networks, ELECTRIC currents |
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| ISSN: | 19961073 |
| DOI: | 10.3390/en12050790 |
| Database: | Complementary Index |
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