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Harmonic Distortion Prediction Model of a Grid- Tie Photovoltaic Inverter Using an Artificial Neural Network (CROSBI ID 260943)

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Žnidarec, Matej ; Klaić, Zvonimir ; Šljivac, Damir ; Dumnić, Boris Harmonic Distortion Prediction Model of a Grid- Tie Photovoltaic Inverter Using an Artificial Neural Network // Energies (Basel), 12 (2019), 5; 790, 19. doi: 10.3390/en12050790

Podaci o odgovornosti

Žnidarec, Matej ; Klaić, Zvonimir ; Šljivac, Damir ; Dumnić, Boris

engleski

Harmonic Distortion Prediction Model of a Grid- Tie Photovoltaic Inverter Using an Artificial Neural Network

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.

power quality ; photovoltaic system ; current harmonics prediction ; artificial neural network

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Podaci o izdanju

12 (5)

2019.

790

19

objavljeno

1996-1073

10.3390/en12050790

Povezanost rada

Elektrotehnika

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