Optimal Defense Strategy Against Load Redistribution Attacks under Attacker’s Resource Uncertainty: A Trilevel Optimization Approach
- Resource Type
- Conference
- Authors
- Su, Jinshun; Xie, Chengzhi; Dehghanian, Payman; Mehrani, Saharnaz
- Source
- 2023 IEEE PES Grid Edge Technologies Conference & Exposition (Grid Edge) Grid Edge Technologies Conference & Exposition (Grid Edge), 2023 IEEE PES. :1-5 Apr, 2023
- Subject
- Power, Energy and Industry Applications
Uncertainty
Programming
Control systems
Power grids
Resource management
Optimization
Cyberattack
Load redistribution (LR) attack
cyber attack
trilevel optimization
chance-constrained programming
Benders decomposition
- Language
The wide deployment of advanced computer technologies and evolving digitalization in power systems monitoring and control will inevitably make the power grid more vulnerable to cyber adversaries. Regarded as a viable cyber attack mechanism against power grids, load redistribution (LR) attack may mislead the power re-dispatch and cause unnecessary load outages. In this research, we develop a strategy for optimal allocation of limited defensive resources to safeguard power systems against LR attacks. The proposed defense scheme against LR attack is formulated as a trilevel optimization problem. To capture the uncertainty of attacking resources, we present a chance-constrained programming formulation where chance constraint is used to capture the possible variations in the attacker’s actions constrained by the uncertain available resources. The Karush- Kuhn-Tucker (KKT) condition and Benders decomposition algorithm are applied to solve the trilevel optimization problem. Case studies on the IEEE 57-bus test system demonstrate the efficiency of the resulting defense decisions against LR attacks.