Artificial Neural Networks to Predict the Power Output of a PV Panel
Joint Authors
Di Falco, Mariavittoria
Lo Brano, Valerio
Ciulla, Giuseppina
Source
International Journal of Photoenergy
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-12, 12 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-01-23
Country of Publication
Egypt
No. of Pages
12
Main Subjects
Abstract EN
The paper illustrates an adaptive approach based on different topologies of artificial neural networks (ANNs) for the power energy output forecasting of photovoltaic (PV) modules.
The analysis of the PV module’s power output needed detailed local climate data, which was collected by a dedicated weather monitoring system.
The Department of Energy, Information Engineering, and Mathematical Models of the University of Palermo (Italy) has built up a weather monitoring system that worked together with a data acquisition system.
The power output forecast is obtained using three different types of ANNs: a one hidden layer Multilayer perceptron (MLP), a recursive neural network (RNN), and a gamma memory (GM) trained with the back propagation.
In order to investigate the influence of climate variability on the electricity production, the ANNs were trained using weather data (air temperature, solar irradiance, and wind speed) along with historical power output data available for the two test modules.
The model validation was performed by comparing model predictions with power output data that were not used for the network's training.
The results obtained bear out the suitability of the adopted methodology for the short-term power output forecasting problem and identified the best topology.
American Psychological Association (APA)
Lo Brano, Valerio& Ciulla, Giuseppina& Di Falco, Mariavittoria. 2014. Artificial Neural Networks to Predict the Power Output of a PV Panel. International Journal of Photoenergy،Vol. 2014, no. 2014, pp.1-12.
https://search.emarefa.net/detail/BIM-1036796
Modern Language Association (MLA)
Lo Brano, Valerio…[et al.]. Artificial Neural Networks to Predict the Power Output of a PV Panel. International Journal of Photoenergy No. 2014 (2014), pp.1-12.
https://search.emarefa.net/detail/BIM-1036796
American Medical Association (AMA)
Lo Brano, Valerio& Ciulla, Giuseppina& Di Falco, Mariavittoria. Artificial Neural Networks to Predict the Power Output of a PV Panel. International Journal of Photoenergy. 2014. Vol. 2014, no. 2014, pp.1-12.
https://search.emarefa.net/detail/BIM-1036796
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1036796