A computational intelligence approach to solar panel modelling
Citation
Ferrari, S., Lazzaroni, M., Piuri, V., Salman, A., Cristaldi, L., Faifer, M., & Toscani, S. (2014). A computational intelligence approach to solar panel modelling. 2014 IEEE International Instrumentation and Measurement Technology Conference (I2MTC) Proceedings (pp. 1261-1266). Piscataway, NJ: IEEE. https://dx.doi.org/10.1109/I2MTC.2014.6860947Abstract
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.
