Reduced-order thermo-electro-chemical modeling of battery energy storage system for performance evaluation and degradation

Abstract Utility-scale Battery Energy Storage Systems (BESS) are increasingly used for peak shaving and grid support. However, conventional BESS modeling based on equivalent circuit models or rule-based control often overlook internal electrochemical and thermal dynamics, failing to capture how grid applications affect cell states. Such simplifications can compromise long-term reliability. This work introduces a simulation framework that embeds a reduced-order electrochemical model: the Single Particle Model with electrolyte (SPMe), to evaluate BESS under realistic operation. The framework tracks electrochemical parameters, revealing how peak shaving duty cycles impacts internal states over time. By linking cell-level physics with system-level operation, the approach enables both accurate performance assessment and insight into the long-term behavior of BESS. Simulation studies with realistic load profiles demonstrate effective peak reduction while monitoring long-term impacts, providing a physics-informed detailed modeling as an alternative to rule-based methods. Developed modeling approach works as a foundation for health or degradation-aware control of grid-connected BESS.