AI-Based Charging Discharging Controller for Lithium Ion Battery in Microgrid Application

Abstract - Integration of lithium-ion batteries into microgrid systems has emerged as a practical solution for grid stability, energy storage, and the integration of renewable energy, particularly solar. However, battery charging and discharging processes need to be controlled wisely and effectively in order to maximize system performance, extend battery life, and improve overall energy efficiency. The AI-based charging-discharging controller described in this work is specifically designed for microgrid applications involving lithium-ion batteries. The proposed approach uses state-of-the-art machine learning algorithms to monitor critical battery parameters, optimise power flow within the microgrid, and forecast energy demand. The controller ensures system efficiency and operating safety by dynamically adjusting charging and discharging rates in response to real-time data such as temperature, load requirements, and state of charge (SOC). Simulation findings show the system's potential to decrease energy waste, extend battery life, and enable the seamless integration of renewable energy sources. The AI-driven approach not only increases microgrid reliability but also contributes to cost-effective and sustainable energy management solutions.