Towards Sustainable Energy Management: Analyzing AI-Based Solutions for PV Systems with Battery in Energy Communities

Abstract

This paper addresses the pressing issue of meeting energy demand sustainably, which has become increasingly challenging in recent years due to the rising prices and limited supply of fossil fuels. In response, the use of distributed renewable energy generation systems has emerged as a potential solution. The European Union has shifted its regulatory focus towards promoting renewable energy communities, as opposed to centralized fossil fuel production. To overcome the variability and unpredictability of renewable sources, electrical energy storage devices are often used, typically Li-ion batteries. Proper sizing and control of batteries and the entire system is crucial for optimal performance. The objective of this paper is to develop a simulation framework suitable for developing AI-based energy management solutions for a grid-connected system with solar cells and a shared battery energy storage that serves the energy needs of multiple residential consumers. The simulation is conducted using actual solar radiation and load data in the Matlab Simulink environment. Finally, the study aims to investigate the impact of various consumption profiles and seasonal variation in solar energy production on battery utilization.