An Enhanced Cloud-Based Digital Twin State Monitoring for Smart Stationary Battery Energy Storage System

Digital twins (DTs) of stationary battery energy storage systems (BESSs) are increasingly recognized for their potential to enhance service lifetime, enable predictive maintenance, and improve end-user services. However, the effectiveness of these systems heavily relies on advanced state monitoring techniques and availability of data to further refine the twin models. This paper presents a state monitoring based on a virtual BESS entity within a cloud-based DT framework. It also explores the integration of real-time data from a physical BESS into the DT framework and evaluates the DT's response to these real-time inputs. Furthermore, this approach aims to enhance the reliability and accuracy of state estimation in BESS DTs. The performance results and the cloud-based DT show less than 2% deviation compared to the physical 50kWh BESS state estimation during concurrent operation.