Abstract
The inherent low conversion efficiency, from solar to electrical energy, of the photovoltaic cells makes the use of techniques and architectures aimed at maximizing the electrical power a photovoltaic array is able to produce at any weather condition mandatory. In order to understand what are the challenging problems cropping up in some modern applications, an overview of the main techniques for photovoltaic arrays modeling is given first. Afterwards, the control strategies for the maximum power point tracking used in commercial products dedicated to photovoltaic strings and modules are compared and their advantages and drawbacks are put into evidence, with a special emphasis on their efficiency. Some methods presented in literature and based on the use of artificial neural networks are compared with more classical ones. Finally, a brief overview of other applications of artificial neural networks to photovoltaic-related problems is also given.
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Keywords
- Radial Basis Function Network
- Fuzzy Logic Control
- Maximum Power Point Tracking
- Maximum Power Point
- Mismatched Condition
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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Petrone, G., Sànchez Pacheco, F.J., Spagnuolo, G. (2013). Real Time Techniques and Architectures for Maximizing the Power Produced by a Photovoltaic Array. In: Apolloni, B., Bassis, S., Esposito, A., Morabito, F. (eds) Neural Nets and Surroundings. Smart Innovation, Systems and Technologies, vol 19. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-35467-0_25
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