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Scaling and integrating digital twin applications for battery energy storage systems from building to city

Author

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  • Kang, Hyuna
  • Jung, Dahyun
  • Choi, Jinwoo
  • Hong, Taehoon

Abstract

Battery Energy Storage Systems (BESS) play a critical role in enhancing the sustainability, flexibility, and resilience of future urban energy systems. As intelligent cyber-physical platforms, digital twin (DT) technologies are emerging as enablers of smart and adaptive energy management through real-time monitoring, predictive control, and life-cycle optimization. However, existing studies and applications of DT-driven BESS remains fragmented across spatial scales, often limited to isolated building- or community applications with low interoperability and scalability. This study presents a systematic review of DT-driven BESS technologies across three spatial scales — building, community, and city — through a comprehensive review of 640 publications. The results identify cross-scale limitations related to data interoperability, control integration, and integrative governance, despite rapid progress in predictive control, real-time optimization, and energy sharing within each scale. To address these gaps, this study proposes a multi-scale technology roadmap and city-scale integrated architecture for scalable DT-driven BESS tailored to advance scalable, interoperable, and policy-linked digital twin systems for energy storage. The proposed roadmap defines short-, mid-, and long-term development directions, emphasizing real-time data synchronization, alignment of bottom-up and top-down control, and the design of interoperable architectures that bridge different spatial levels. This study provides a strategic foundation for the evolution of DT-driven BESS from isolated control tools to intelligent infrastructures that enhance urban energy resilience, carbon neutrality, and the achievement of smart energy policy objectives.

Suggested Citation

  • Kang, Hyuna & Jung, Dahyun & Choi, Jinwoo & Hong, Taehoon, 2026. "Scaling and integrating digital twin applications for battery energy storage systems from building to city," Renewable and Sustainable Energy Reviews, Elsevier, vol. 229(C).
    • Handle: RePEc:eee:rensus:v:229:y:2026:i:c:s1364032125013358
    DOI: 10.1016/j.rser.2025.116662
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    1. Ping, Dazhou & Li, Chaosu & Yu, Xiaojun & Liu, Zhengxuan & Tu, Ran & Zhou, Yuekuan, 2025. "City-scale information modelling for urban energy resilience with optimal battery energy storages in Hong Kong," Applied Energy, Elsevier, vol. 378(PA).
    2. Walker, Awnalisa & Kwon, Soongeol, 2021. "Analysis on impact of shared energy storage in residential community: Individual versus shared energy storage," Applied Energy, Elsevier, vol. 282(PA).
    3. Li, Wei & Li, Yongsheng & Garg, Akhil & Gao, Liang, 2024. "Enhancing real-time degradation prediction of lithium-ion battery: A digital twin framework with CNN-LSTM-attention model," Energy, Elsevier, vol. 286(C).
    4. Bayer, Daniel R. & Pruckner, Marco, 2024. "Data-driven heat pump retrofit analysis in residential buildings: Carbon emission reductions and economic viability," Applied Energy, Elsevier, vol. 373(C).
    5. Kang, Hyuna & Jung, Seunghoon & Lee, Minhyun & Hong, Taehoon, 2022. "How to better share energy towards a carbon-neutral city? A review on application strategies of battery energy storage system in city," Renewable and Sustainable Energy Reviews, Elsevier, vol. 157(C).
    6. Mahmoud S. Abdelrahman & Ibtissam Kharchouf & Hossam M. Hussein & Mustafa Esoofally & Osama A. Mohammed, 2024. "Enhancing Cyber-Physical Resiliency of Microgrid Control under Denial-of-Service Attack with Digital Twins," Energies, MDPI, vol. 17(16), pages 1-25, August.
    7. Lin, Xiaojie & Liu, Sibin & Lu, Shuowei & Li, Zhongbo & Zhou, Yi & Yu, Zitao & Zhong, Wei, 2020. "A study on operation control of urban centralized heating system based on cyber-physical systems," Energy, Elsevier, vol. 191(C).
    8. Elda Cina & Ersin Elbasi & Gremina Elmazi & Zakwan AlArnaout, 2025. "The Role of AI in Predictive Modelling for Sustainable Urban Development: Challenges and Opportunities," Sustainability, MDPI, vol. 17(11), pages 1-39, June.
    9. Lv, Zhihan & Cheng, Chen & Lv, Haibin, 2023. "Digital twins for secure thermal energy storage in building," Applied Energy, Elsevier, vol. 338(C).
    10. Berecibar, M. & Gandiaga, I. & Villarreal, I. & Omar, N. & Van Mierlo, J. & Van den Bossche, P., 2016. "Critical review of state of health estimation methods of Li-ion batteries for real applications," Renewable and Sustainable Energy Reviews, Elsevier, vol. 56(C), pages 572-587.
    11. Nweye, Kingsley & Sankaranarayanan, Siva & Nagy, Zoltan, 2023. "MERLIN: Multi-agent offline and transfer learning for occupant-centric operation of grid-interactive communities," Applied Energy, Elsevier, vol. 346(C).
    12. Paolo Tenti & Tommaso Caldognetto, 2022. "Generalized Control of the Power Flow in Local Area Energy Networks," Energies, MDPI, vol. 15(4), pages 1-21, February.
    13. Hao Jiang & Rudy Tjandra & Chew Beng Soh & Shuyu Cao & Donny Cheng Lock Soh & Kuan Tak Tan & King Jet Tseng & Sivaneasan Bala Krishnan, 2024. "Digital Twin of Microgrid for Predictive Power Control to Buildings," Sustainability, MDPI, vol. 16(2), pages 1-23, January.
    14. Kang, Hyuna & Jung, Seunghoon & Kim, Hakpyeong & Hong, Juwon & Jeoung, Jaewon & Hong, Taehoon, 2023. "Multi-objective sizing and real-time scheduling of battery energy storage in energy-sharing community based on reinforcement learning," Renewable and Sustainable Energy Reviews, Elsevier, vol. 185(C).
    15. Semeraro, Concetta & Aljaghoub, Haya & Abdelkareem, Mohammad Ali & Alami, Abdul Hai & Olabi, A.G., 2023. "Digital twin in battery energy storage systems: Trends and gaps detection through association rule mining," Energy, Elsevier, vol. 273(C).
    16. Fei Tao & Fangyuan Sui & Ang Liu & Qinglin Qi & Meng Zhang & Boyang Song & Zirong Guo & Stephen C.-Y. Lu & A. Y. C. Nee, 2019. "Digital twin-driven product design framework," International Journal of Production Research, Taylor & Francis Journals, vol. 57(12), pages 3935-3953, June.
    17. Kang, Hyuna & Jung, Seunghoon & Kim, Hakpyeong & Jeoung, Jaewon & Hong, Taehoon, 2024. "Reinforcement learning-based optimal scheduling model of battery energy storage system at the building level," Renewable and Sustainable Energy Reviews, Elsevier, vol. 190(PA).
    18. Yang, Yuqing & Bremner, Stephen & Menictas, Chris & Kay, Merlinde, 2018. "Battery energy storage system size determination in renewable energy systems: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 91(C), pages 109-125.
    19. Naseri, F. & Gil, S. & Barbu, C. & Cetkin, E. & Yarimca, G. & Jensen, A.C. & Larsen, P.G. & Gomes, C., 2023. "Digital twin of electric vehicle battery systems: Comprehensive review of the use cases, requirements, and platforms," Renewable and Sustainable Energy Reviews, Elsevier, vol. 179(C).
    20. Timothé Gronier & William Maréchal & Christophe Geissler & Stéphane Gibout, 2022. "Usage of GAMS-Based Digital Twins and Clustering to Improve Energetic Systems Control," Energies, MDPI, vol. 16(1), pages 1-17, December.
    21. Solon Solomou & Ulysses Sengupta, 2025. "Simulating Complex Urban Behaviours With AI: Incorporating Improved Intelligent Agents in Urban Simulation Models," Urban Planning, Cogitatio Press, vol. 10.
    22. Henni, Sarah & Staudt, Philipp & Weinhardt, Christof, 2021. "A sharing economy for residential communities with PV-coupled battery storage: Benefits, pricing and participant matching," Applied Energy, Elsevier, vol. 301(C).
    23. Hanif, Sarmad & Alam, M.J.E. & Roshan, Kini & Bhatti, Bilal A. & Bedoya, Juan C., 2022. "Multi-service battery energy storage system optimization and control," Applied Energy, Elsevier, vol. 311(C).
    24. Kaluthanthrige, Roshani & Rajapakse, Athula D., 2021. "Evaluation of hierarchical controls to manage power, energy and daily operation of remote off-grid power systems," Applied Energy, Elsevier, vol. 299(C).
    25. Reniers, Jorn M. & Howey, David A., 2023. "Digital twin of a MWh-scale grid battery system for efficiency and degradation analysis," Applied Energy, Elsevier, vol. 336(C).
    26. Granacher, Julia & Nguyen, Tuong-Van & Castro-Amoedo, Rafael & Maréchal, François, 2022. "Overcoming decision paralysis—A digital twin for decision making in energy system design," Applied Energy, Elsevier, vol. 306(PA).
    27. Sen, Sachidananda & Kumar, Maneesh & Vedik, Basetti & Shiva, Chandan K. & Prajapati, Arvind Kumar, 2024. "Adaptive-DMPC based energy management and pre-installation techno-economic analysis of a grid-tied cyber-physical community microgrid," Chaos, Solitons & Fractals, Elsevier, vol. 187(C).
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