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Improved Modeling of I-V Characteristic Based on Artificial Neural Network in Photovoltaic Systems  

Park, Jiwon (Department of System Semiconductor Engineering, Sangmyung University)
Lee, Jonghwan (Department of System Semiconductor Engineering, Sangmyung University)
Publication Information
Journal of the Semiconductor & Display Technology / v.21, no.3, 2022 , pp. 135-139 More about this Journal
Abstract
The current-voltage modeling plays an important role in characterizing photovoltaic systems. A solar cell has a nonlinear characteristic with various parameters influenced by the external environments such as the irradiance and the temperature. In order to accurately predict current-voltage characteristics at low irradiance, the artificial neural networks are applied to effectively quantify nonlinear behaviors. In this paper, a multi-layer perceptron scheme that can make accurate predictions is employed to learn complex formulas for large amounts of continuous data. The simulated results of artificial neural networks model show the accuracy improvement by using MATLAB/Simulink.
Keywords
Two diode model; Photovoltaic System; Artificial Neural Network; Multi-Layer Perceptron; Maximum Power Point; I-V Curve;
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