| Issue |
E3S Web Conf.
Volume 297, 2021
The 4th International Conference of Computer Science and Renewable Energies (ICCSRE'2021)
|
|
|---|---|---|
| Article Number | 01037 | |
| Number of page(s) | 5 | |
| DOI | https://doi.org/10.1051/e3sconf/202129701037 | |
| Published online | 22 September 2021 | |
Management of battery charging and discharging in a photovoltaic system with variable power demand using artificial neural networks
1 Hassan First University of Settat, The Faculty of Sciences and Technology, Laboratory of Engineering, Industrial Management and Innovation (IMII), Morocco
2 Hassan First University of Settat, The Faculty of Sciences and Technology, Laboratory of Radiation-Matter and Instrumentation (RMI), Morocco
3 Hassan First University of Settat, The Faculty of Sciences and Technology, Laboratory of Research Watch for Emerging Technologies (VETE), Morocco
* Corresponding author: author@email.org
The energy is the basis of all human activities. Nowadays, much of the world’s energy demand is taken from fossil fuels. However, fossil fuel reserves are limited. The use of solar photovoltaic energy is therefore a necessity for the future. With the rapid increase of photovoltaic or hybrid systems, solar batteries provide an unforgettable energy storage tool in this type of systems in order to ensure an energy supply to consumers. Due to the sensitivity of solar batteries and the random operation of photovoltaic systems that depend on solar irradiance, control and management strategies are quite important. In this paper, we present a technique based on artificial neural networks to control the charging and discharging of solar batteries in order to protect the batteries from overcharging and deep discharging. In addition, ensuring continuous supply to consumers. The proposed model is developed and simulated in Matlab/Simulink.
© The Authors, published by EDP Sciences, 2021
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