R&D Department, ZheJiang HuaBang IOT Technology Co., Ltd, Wenzhou, Zhejiang, 325103, China
Email: 15258043575@163.com (S.S.P.)
*Corresponding author
Manuscript received October 28, 2024; accepted May 7, 2025; published August 18, 2025.
Abstract—Digital twin technology is transforming the management and optimisation of Battery Energy Storage Systems (BESS) in on-grid applications. This paper presents the design and simulation of a digital twin for BESS with the aim of identifying system performance, reliability and operational efficiency through mathematical modelling. A detailed simulation-based architecture is developed, enabling predictive analytics and control. The digital twin uses a Single Particle Model (SPM) to computationally simulate the electrochemical behaviour of battery cells, providing insight into critical parameters such as State of Charge (SoC), State of Health (SoH) and degradation over time. In addition, a Python-based simulation model is examined to analyse and optimise energy flows within the grid. This study demonstrates how simulation-driven digital twin technology can enhance decision-making and system control in on-grid BESS applications, making it useful for academic studies and practical implementation.
Keywords—digital twin, battery energy storage system, on-grid application, single particle model, python, SoC, SoH, predictive maintenance, energy management system
Cite: Singh Sathya Prakash, Yu Zhenyong, Li Chengqiang, Ke Fei, Dong Zili, and Zhao Shaozhong, "Digital Twin Simulation of a Battery Energy Storage System for On-Grid Applications," International Journal of Engineering and Technology, vol. 17, no. 3, pp. 169-176, 2025.
Copyright © 2025 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (
CC BY 4.0). 
