Cascading Failure Propagation and Mitigation Strategies in Power Systems

Li, Meixuan Jade; Tse, Chi K.; Liu, Dong; Zhang, Xi

doi:10.1109/jsyst.2023.3248044

Cited by 9 publications

(1 citation statement)

References 33 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Subsequently, many researchers built on this concept and used complex network theory to study the mechanisms of cascading failures in various systems. They proposed cascading failure models such as load capacity models [10,11], epidemic models [12], OPA failure models (ORNL-PSERC-Alaska, OPA), sandpile models [13], and power flow models [14] to explain the causes behind cascading failure phenomena. Regarding the common load capacity models, various researchers have proposed different load redistribution strategies.…”

Section: Introductionmentioning

confidence: 99%

Analysis of Controllability in Cyber–Physical Power Systems under a Novel Load-Capacity Model

Ge,

Li,

et al. 2023

Processes

View full text Add to dashboard Cite

In cyber–physical power systems (CPPSs), system collapse can occur as a result of a failure in a particular component. In this paper, an approach is presented to build the load-capacity model of CPPSs using the concept of electrical betweenness and information entropy, which takes into account real-time node loads and the allocation of power and information flows within CPPSs. By introducing an innovative load redistribution strategy and comparing it with conventional load distribution strategies, the superior effectiveness of the proposed strategy in minimizing system failures and averting system collapses has been demonstrated. The controllability of the system after cascading failures under different coupling strategies and capacity parameters is investigated through the analysis of different information network topologies and network parameters. It was observed that CPPSs constructed using small-world networks, which couple high-degree nodes from the information network to high-betweenness nodes from the power grid, exhibit improved resilience. Furthermore, increasing the capacity parameter of the power network yields more favorable results compared to increasing the capacity parameter of the information network. In addition, our research results are validated using the IEEE 39-node system and the Chinese 132-node system.

show abstract