Energy Storage System

Energy storage systems (ESS) are crucial for integrating renewable energy sources and improving grid stability, with research focusing on optimizing their operation and extending their lifespan. Current efforts employ advanced control strategies, such as deep reinforcement learning (including attention mechanisms) and model predictive control, to maximize economic benefits through energy arbitrage and minimize curtailment of renewable energy sources. These advancements, coupled with improved methods for predicting remaining useful life (e.g., using machine learning), are vital for enhancing the efficiency and reliability of ESS across diverse applications, from electric vehicles to residential buildings and large-scale grids. The development of interpretable models is also a key focus to improve the practical applicability of these optimization strategies.