DocumentCode :
187261
Title :
A computational intelligence approach to solar panel modelling
Author :
Ferrari, Silvia ; Lazzaroni, M. ; Piuri, V. ; Salman, A. ; Cristaldi, L. ; Faifer, Marco ; Toscani, Sergio
Author_Institution :
Univ. degli Studi di Milano, Milan, Italy
fYear :
2014
fDate :
12-15 May 2014
Firstpage :
1261
Lastpage :
1266
Abstract :
The power produced by a solar panel depends on several parameters. In order to optimize the production, the ability to operate in the Maximum Power Point (MPP) condition is requested. The ability to identify and reach the MPP condition is therefore critical to an efficient conversion of the photovoltaic energy. In this paper, several computational intelligence paradigms are challenged in the task of identifying the MPP power from the working condition directly measurable from the solar panel, such as the voltage, V, the current, I, and the temperature, T, of the panel.
Keywords :
maximum power point trackers; solar cells; MPP condition; computational intelligence approach; maximum power point condition; photovoltaic energy; solar panel modelling; Computational intelligence; Computational modeling; Current measurement; Predictive models; Temperature measurement; Testing; Training;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Instrumentation and Measurement Technology Conference (I2MTC) Proceedings, 2014 IEEE International
Conference_Location :
Montevideo
Type :
conf
DOI :
10.1109/I2MTC.2014.6860947
Filename :
6860947
Link To Document :
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