Modeling Method for the Coupling Relations of Microgrid Cyber-Physical Systems Driven by Hybrid Spatiotemporal Events
Xiaoyong Bo, Xiaoyu Chen, Huashun Li, Yunchang Dong, Zhaoyang Qu, Lei, Wang, and Yang Li

TL;DR
This paper introduces a novel modeling approach for microgrid cyber-physical systems that captures the dynamic coupling of information and energy flows driven by hybrid spatiotemporal events, improving accuracy in risk and failure analysis.
Contribution
It presents a hybrid automata-based modeling method that considers the cyclical conversion and multi-agent architecture of microgrid CPS, addressing limitations of static network models.
Findings
Model accurately describes spatiotemporal evolution of microgrid CPS.
Effective in simulating false data injection attack scenarios.
Enhances understanding of risk propagation and safety assessment.
Abstract
The essence of the microgrid cyber-physical system (CPS) lies in the cyclical conversion of information flow and energy flow. Most of the existing coupling models are modeled with static networks and interface structures, in which the closed-loop data flow characteristic is not fully considered. It is difficult for these models to accurately describe spatiotemporal deduction processes, such as microgrid CPS attack identification, risk propagation, safety assessment, defense control, and cascading failure. To address this problem, a modeling method for the coupling relations of microgrid CPS driven by hybrid spatiotemporal events is proposed in the present work. First, according to the topological correlation and coupling logic of the microgrid CPS, the cyclical conversion mechanism of information flow and energy flow is analyzed, and a microgrid CPS architecture with multi-agents as the…
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