![](/images/graphics-bg.png)
Hybrid Neural Network Approach Based Tool for the Modelling of Photovoltaic Panels
Joint Authors
Laudani, Antonino
Lozito, Gabriele Maria
Riganti Fulginei, Francesco
Salvini, Alessandro
Source
International Journal of Photoenergy
Issue
Vol. 2015, Issue 2015 (31 Dec. 2015), pp.1-10, 10 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2015-02-22
Country of Publication
Egypt
No. of Pages
10
Main Subjects
Abstract EN
A hybrid neural network approach based tool for identifying the photovoltaic one-diode model is presented.
The generalization capabilities of neural networks are used together with the robustness of the reduced form of one-diode model.
Indeed, from the studies performed by the authors and the works present in the literature, it was found that a direct computation of the five parameters via multiple inputs and multiple outputs neural network is a very difficult task.
The reduced form consists in a series of explicit formulae for the support to the neural network that, in our case, is aimed at predicting just two parameters among the five ones identifying the model: the other three parameters are computed by reduced form.
The present hybrid approach is efficient from the computational cost point of view and accurate in the estimation of the five parameters.
It constitutes a complete and extremely easy tool suitable to be implemented in a microcontroller based architecture.
Validations are made on about 10000 PV panels belonging to the California Energy Commission database.
American Psychological Association (APA)
Laudani, Antonino& Lozito, Gabriele Maria& Riganti Fulginei, Francesco& Salvini, Alessandro. 2015. Hybrid Neural Network Approach Based Tool for the Modelling of Photovoltaic Panels. International Journal of Photoenergy،Vol. 2015, no. 2015, pp.1-10.
https://search.emarefa.net/detail/BIM-1066493
Modern Language Association (MLA)
Laudani, Antonino…[et al.]. Hybrid Neural Network Approach Based Tool for the Modelling of Photovoltaic Panels. International Journal of Photoenergy No. 2015 (2015), pp.1-10.
https://search.emarefa.net/detail/BIM-1066493
American Medical Association (AMA)
Laudani, Antonino& Lozito, Gabriele Maria& Riganti Fulginei, Francesco& Salvini, Alessandro. Hybrid Neural Network Approach Based Tool for the Modelling of Photovoltaic Panels. International Journal of Photoenergy. 2015. Vol. 2015, no. 2015, pp.1-10.
https://search.emarefa.net/detail/BIM-1066493
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1066493