TY - GEN
T1 - From Vision to Application
T2 - 3rd IEEE International Conference on Power Science and Technology, ICPST 2025
AU - Wang, Zheng
AU - Zhou, Sicheng
AU - Zhuang, Kanqin
AU - Chen, Hao
AU - Yang, Nan
AU - Liu, Lu
N1 - Publisher Copyright:
© 2025 IEEE.
PY - 2025
Y1 - 2025
N2 - The “Digital Intelligent Resilient Grid” (DIRG), proposed by the State Grid Corporation of China, aims to enhance the reliability, flexibility, and sustainability of power systems through advanced digital technologies. This paper systematically reviews key DIRG technologies-AI, digital twins, blockchain, cloud-edge computing, advanced communication, grid security, and coordinated control of source-grid-load-storage. We assess the maturity of these technologies using logistic curve fitting on patent data, complemented by expert opinions. Results reveal varied developmental stages, with blockchain and digital twins maturing faster than edge computing and coordinated control. Finally, we outline targeted future directions such as AI-driven automation, decentralized energy management, and intelligent dispatch. This study provides a quantitative foundation and strategic roadmap to guide the digital transformation of power systems.
AB - The “Digital Intelligent Resilient Grid” (DIRG), proposed by the State Grid Corporation of China, aims to enhance the reliability, flexibility, and sustainability of power systems through advanced digital technologies. This paper systematically reviews key DIRG technologies-AI, digital twins, blockchain, cloud-edge computing, advanced communication, grid security, and coordinated control of source-grid-load-storage. We assess the maturity of these technologies using logistic curve fitting on patent data, complemented by expert opinions. Results reveal varied developmental stages, with blockchain and digital twins maturing faster than edge computing and coordinated control. Finally, we outline targeted future directions such as AI-driven automation, decentralized energy management, and intelligent dispatch. This study provides a quantitative foundation and strategic roadmap to guide the digital transformation of power systems.
KW - digital intelligent resilient grid
KW - logistic curve fitting
KW - maturity assessment
UR - https://www.scopus.com/pages/publications/105013623527
U2 - 10.1109/ICPST65050.2025.11089443
DO - 10.1109/ICPST65050.2025.11089443
M3 - Conference contribution
AN - SCOPUS:105013623527
T3 - 2025 IEEE 3rd International Conference on Power Science and Technology, ICPST 2025
SP - 1214
EP - 1220
BT - 2025 IEEE 3rd International Conference on Power Science and Technology, ICPST 2025
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 16 May 2025 through 18 May 2025
ER -