TY  - EJOU
AU  - Li, Jin 
AU  - Liang, Xiaowen 
AU  - Liu, Chunfang 
AU  - Wu, Hongyao 
AU  - Kuang, Zilun 
AU  - Liang, Kunquan 
AU  - Jiang, Bo 

TI  - Risk Assessment and Probabilistic Two-Stage Robust Optimization for Defense Resource Allocation in Intelligent Substations under Extreme Natural Disasters
T2  - Energy Engineering

PY  - 
VL  - 
IS  - 
SN  - 1546-0118

AB  - With the increasing need for resilience enhancement in modern power systems under extreme natural disasters, this paper proposes an integrated framework for risk assessment and pre-disaster defense resource allocation in intelligent substations. The framework first performs preliminary abnormality screening and probability elicitation, then fuses interval evidence through Dempster–Shafer (D–S) theory, subsequently propagates the resulting probabilistic information through a knowledge-driven Bayesian network (BN), and finally incorporates the inferred tripping risk of the intelligent electronic device for circuit breaker control (CB IED) into a probabilistic two-stage robust optimization (PTSRO) model for pre-disaster defense resource allocation. Within this framework, a knowledge-driven Bayesian network is developed to characterize the major anomaly propagation process from physical-side abnormalities to CB IED tripping events, thereby providing a more decision-relevant probabilistic risk description for substation protection. Furthermore, a probability-informed PTSRO is established to determine the optimal pre-disaster defense resource allocation under limited defense resources and adverse disruption conditions. To improve computational tractability, the proposed model is reformulated into a mixed-integer linear form and solved using a column-and-constraint generation (C&CG)-based procedure. Flooding is selected as the representative hazard scenario in the case studies. Results on the IEEE 24-bus and IEEE 118-bus systems show that the proposed framework can effectively reduce disaster-risk values and provide useful support for substation-oriented defense planning.
KW  - Power grid resilience; robust optimization; risk assessment; Bayesian network; circuit breaker; intelligent electronic device

DO  - 10.32604/ee.2026.080799