A small-signal model of a solar cell. (November 2014)

• Record Type: Journal Article
• Authors: Andrejević Stošović, Miona; Litovski, Ivan; Lukač, Duško; Dimitrijević, Marko; Litovski, Vančo
• Is Part Of: Simulation. Volume 90:Number 11(2014:Nov.)
• Page Start: 1231
• Page End: 1243
• Publication Date: 2014-11
• Subjects: Artificial neural networks -- frequency domain simulation -- photovoltaic cells -- semiconductor device modeling -- time domain simulation; Computer simulation -- Periodicals; 003.3
• DOI: 10.1177/0037549714551290
• Languages: English
• ISSNs: 0037-5497

Abstract

Starting with the experience that the output voltage and the output current of a photovoltaic panel are not pure direct current constants due to the inevitable connection to a converter (or inverter) that is working as a switching system, we came to the conclusion that interest exists for the behavior of the solar cell at the frequencies of the harmonics of the converter's switching frequency, which is subject to change according to the maximum power-point tracking. In other words, a need exists for frequency domain characterization of the solar cell, for which a linear small-signal model is necessary. To enable simulation for small signals, development of a linear reactive model was considered. Since a one-diode large-signal model already exists, it was used as a basis for the extraction of the parameters of the small-signal model. The new model was represented in the form of a parallel RC two-terminal circuit, the R and C being functions of the photocurrent (acting as a map of the illumination) and the diode voltage. Since the R and C of the model are quiescent-point dependent, their values as a function of the illumination and the diode voltages were approximated by artificial neural networks (ANNs). Separate ANNs were created for modeling R and C . To verify the model, two small-signal simulations were performed. The first one was done with the existing nonlinear model, while the second was done with the new linear model (running the ANNs). Excellent agreement was obtained.