Optimal Defense Strategy Against Load Redistribution Attacks under Attacker’s Resource Uncertainty: A Trilevel Optimization Approach

Abstract

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.