Technical Report on Resilient and Secure Large-Scale Energy Internet Systems

📅 2026-08-13
📈 Citations: 0
Influential: 0
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🤖 AI Summary
In the context of deep digitalization, large-scale energy internet systems face significant cyber-physical security and resilience challenges due to the tight coupling among power, information, and market layers. This work proposes a comprehensive modeling and decision-making framework that integrates energy storage coordination, multidimensional resilience, and electricity price forecasting. It introduces a graph-computation-based attack-resilient information routing mechanism and, for the first time, incorporates artificial intelligence trustworthiness assurance into the security and resilience research paradigm for energy internet systems. By synergistically combining cyber-physical system modeling, AI security techniques, and multilayer coordinated control strategies, the project establishes a holistic technical framework tailored to the security and resilience needs of large-scale energy internet infrastructures, thereby providing critical support for standardization efforts and regulatory policy development.
📝 Abstract
This IEEE PES Task Force report examines the security and resilience of large-scale Energy Internet (EI) systems, in which electricity, information, and market layers are tightly coupled through pervasive digitalization. The report characterizes the EI cyber-physical threat landscape and surveys detection, assurance, and mitigation techniques, presents modeling, control, and decision-making frameworks that capture cyber-physical interdependencies, including storage integration, multi-dimensional resilience, and electricity price forecasting, examines adversarial risks and trustworthy deployment of artificial intelligence, and introduces graph-based, attack-resilient information routing. The report closes with recommendations for research, standardization, and regulatory efforts needed to realize a resilient and secure large-scale EI.
Problem

Research questions and friction points this paper is trying to address.

Energy Internet
cyber-physical security
resilience
adversarial risks
trustworthy AI
Innovation

Methods, ideas, or system contributions that make the work stand out.

cyber-physical interdependencies
attack-resilient routing
multi-dimensional resilience
trustworthy AI
graph-based information routing
I
Ioannis Zografopoulos
University of Massachusetts Boston, Boston, MA, USA.
K
Karen Largman
University of Massachusetts Boston, Boston, MA, USA.
I
Isaac Ortega Romero
University of Massachusetts Boston, Boston, MA, USA.
S
S M Zia Ur Rashid
The University of Tulsa, Tulsa, OK, USA.
Y
Yexiang Chen
University of Warwick, Coventry, UK.
George Fragkos
George Fragkos
Sandia National Laboratories, Albuquerque, NM, USA.
C
Charalambos Konstantinou
King Abdullah University of Science and Technology (KAUST), Thuwal, KSA.
Subhash Lakshminarayana
Subhash Lakshminarayana
University of Warwick, School of Engineering
Cyber-Physical system securityWireless Communications
J
Juan Ospina
Orennia, USA.
A
Airin Rahman
University of Central Florida, Orlando, FL, USA.
Suman Rath
Suman Rath
The University of Tulsa
Energy SystemsCybersecurityArtificial Intelligence
V
Vivek Kumar Singh
National Laboratory of the Rockies, USA.
Mucun Sun
Mucun Sun
Idaho National Laboratory
Energy informatics Deep/Machine learningDeterministic/Probabilistic ForecastingPower system big
Wei Sun
Wei Sun
Professor of Electrical Engineering, University of Central Florida
Power System Restoration and Self-healingCyber-Physical System Resilience and Security