Real-Time Hardware-in-the-Loop Modeling and Emulation for Utility-Scale Energy Storage Systems: A Review, Challenges and Path Forward

This work explores battery modeling and emulation techniques for real-time simulation of utility-scale Battery Energy Storage Systems (BESS) in a Hardware-in-the-Loop (HIL) environment. As the adoption of distributed energy resources continues to grow, the demand for efficient and scalable energy storage solutions becomes increasingly critical. Batteries, as a key component of energy infrastructure, require precise models to evaluate performance, reliability, and fault-handling capabilities, particularly in industrial and utility-scale applications, where investment and operational decisions depend on results from accurate simulation. The paper examines a variety of battery modeling approaches, including Equivalent Circuit Models (ECMs), Electrochemical Models (EMs), and data-driven methods such as neural networks. These models are analyzed for their roles in simulating charging, discharging, and fault conditions of battery modules. Additionally, this work evaluates the limitations of each modeling approach, focusing on the trade-offs between accuracy, computational efficiency, and scalability for real-time simulation and emulation. It also includes an in-depth exploration of battery models suitable for real-time HIL implementation, alongside a comparative analysis of commercially available emulators, highlighting their strengths, hardware constraints, and industrial relevance. This study underscores the importance of emulation accuracy, scalability, and real-time performance, while addressing key challenges such as parameter estimation, thermal impact, non-linear characteristics, and model validation. These insights pave the way for advanced modeling approaches, such as Digital Twins (DTs), and support informed BESS technology adoption in smart grid and industrial energy systems.