Enhancing the robustness of cyber–physical power systems: From the perspective of information flow control
In Cyber–Physical Power Systems (CPPSs), the deep coupling of physical and cyber systems can trigger cascading failures, resulting in cross-space fault propagation and an elevated risk of system collapse. This paper explores how controlling the information flow in the cyber layer can enhance the robustness of CPPSs during such cascading failures. First, the Software Defined Networking-enabled CPPS (SDN-enabled CPPS) model, which integrates information flow control, has been established to describe the interdependent relationship between cyber and physical systems concerning power supply, monitoring, and control. Corresponding to the power flow control strategy, an information flow control model was established to maximize the observability recovery of the power grid. Second, based on the inverse-time overload protection of power lines and the latency of information flow control, a timeliness model for information flow control was proposed. Subsequently, a CPPS robustness assessment method, which incorporates information flow control, was presented, with the load loss rate serving as the evaluation metric. Finally, the simulation results for the IEEE-39 and IEEE-118 systems reveal average load loss reductions of 5.20% and 6.28% in single-fault scenarios, and 6.33% and 6.66% in multiple-fault scenarios. This indicates that information flow control effectively mitigates load loss and enhances the robustness of CPPSs.
Authors
- Siqi Wan
- Shaoyan Li (ORCID: https://orcid.org/0000-0003-1715-1561)
- Huibin Jia (ORCID: https://orcid.org/0000-0002-5809-2572)
- Jiahe Li (ORCID: https://orcid.org/0000-0003-4131-3356)
- Weiran Hou (ORCID: https://orcid.org/0009-0000-3454-6341)
- Longyue Su
Publication Details
- Journal
- International Journal of Electrical Power & Energy Systems
- Published
- 2025-09-18
- DOI
- https://doi.org/10.1016/j.ijepes.2025.111082
- Citations
- 1
- Primary Topic
- Smart Grid Security and Resilience
- Type
- article
- Field-Weighted Citation Impact
- 1.21