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