Battery Optimization via AI Algorithms

Overview

Energy storage systems require sophisticated optimization algorithms to maximize performance and grid stability. This talk examines how AI revolutionizes battery management through advanced state estimation, predictive maintenance, and optimal charging strategies. We explore machine learning for battery degradation modeling, reinforcement learning for energy arbitrage optimization, and neural networks for performance prediction. The session covers AI-driven grid-scale battery management, computer vision for automated inspection, and practical applications including distributed storage integration and electric vehicle charging optimization.