TY - GEN
T1 - Impact of Community Structure on Robustness of Power Systems
AU - Wang, Yuchen
AU - Liu, Wenshuang
AU - Zhang, Xi
AU - Shan, Xiwen
AU - Wang, Tiezhu
AU - Yang, Jie
N1 - Publisher Copyright:
© 2026 IEEE.
PY - 2026
Y1 - 2026
N2 - Modern power grids are expanding and tightly interconnected, making cascading failures the leading cause of large blackouts and a severe threat to secure operation. Network science shows that grid topology - especially community structure - critically shapes fault propagation. This paper systematically examines how community structure affects power-system robustness against cascading failures. First, we propose simple rules to build large-scale grids ranging from random to strongly modular networks, mirroring realistic topologies. Second, a DC power-flow cascade model, coupled with Monte Carlo simulations, reproduces and statistically analyzes the post-disturbance evolution. Finally, we adopt the power-loss ratio (RBS) as an index to quantify and compare robustness, assessing how communities inhibit fault spread and explaining the causes. Results reveal that networks with stronger communities exhibit smaller average power losses and retain higher structural integrity during cascades; clear community boundaries isolate fault zones and block further spread, significantly enhancing grid robustness and resilience. This paper provides theoretical guidance and practical strategies for power grid topology design, enhancing disaster resistance.
AB - Modern power grids are expanding and tightly interconnected, making cascading failures the leading cause of large blackouts and a severe threat to secure operation. Network science shows that grid topology - especially community structure - critically shapes fault propagation. This paper systematically examines how community structure affects power-system robustness against cascading failures. First, we propose simple rules to build large-scale grids ranging from random to strongly modular networks, mirroring realistic topologies. Second, a DC power-flow cascade model, coupled with Monte Carlo simulations, reproduces and statistically analyzes the post-disturbance evolution. Finally, we adopt the power-loss ratio (RBS) as an index to quantify and compare robustness, assessing how communities inhibit fault spread and explaining the causes. Results reveal that networks with stronger communities exhibit smaller average power losses and retain higher structural integrity during cascades; clear community boundaries isolate fault zones and block further spread, significantly enhancing grid robustness and resilience. This paper provides theoretical guidance and practical strategies for power grid topology design, enhancing disaster resistance.
KW - Cascading Failures
KW - Community Structure
KW - Fault Containment
KW - Power System Robustness
UR - https://www.scopus.com/pages/publications/105043508772
U2 - 10.1109/ISCAS66217.2026.11562438
DO - 10.1109/ISCAS66217.2026.11562438
M3 - Conference contribution
AN - SCOPUS:105043508772
T3 - Proceedings - IEEE International Symposium on Circuits and Systems
SP - 2253
EP - 2257
BT - ISCAS 2026 - 2026 IEEE International Symposium on Circuits and Systems
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2026 IEEE International Symposium on Circuits and Systems, ISCAS 2026
Y2 - 24 May 2026 through 27 May 2026
ER -