| Issue |
E3S Web of Conf.
Volume 547, 2024
International Conference on Sustainable Green Energy Technologies (ICSGET 2024)
|
|
|---|---|---|
| Article Number | 03017 | |
| Number of page(s) | 5 | |
| Section | Energy | |
| DOI | https://doi.org/10.1051/e3sconf/202454703017 | |
| Published online | 09 July 2024 | |
Utilizing Artificial Neural Networks for Intelligent Battery Energy Storage Control in Microgrid Energy Management
1 SRM Madurai college for Engineering and Technology rajee.gopalan@gmail.com, Pottapalayam, Sivagangai District
2 Fatima Michael college of Engineering and Technology rani.nisha@gmail.com, Madurai.
* Corresponding author: rajee.gopalan@gmail.com
This paper presents an intelligent control approach for a microgrid system comprising photovoltaic panels, grid connection, and lithium-ion battery energy storage. The energy management strategy revolves around regulating the charging and discharging of by incorporating an advanced controller into the DC/DC two directional converter. An essential aspect of this approach entails the incorporation of Artificial Neural networks (ANN) for accurate predetermination of the charge state of the battery and for controlling the two directional converter. Output from simulations conducted in the MATLAB/ Simulink environment illustrate its effectiveness, also their reliability of the proposed control method.
© The Authors, published by EDP Sciences, 2024
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