Risk-Based Mitigation of Load Curtailment Cyber Attack Using Intelligent Agents in a Shipboard Power System

Abstract

Modern shipboard power systems (SPSs) with advanced cyber infrastructure need urgent attention because they have higher risk of cyber attacks. In particular, false data injection (FDI) attacks can interfere with state estimation by tampering with measurement devices, or they may also directly target the central control system. This paper proposes a twofold strategy to mitigate the effects of such an unconventional FDI attack, using battery to actively reduce load curtailment. To detect signs of malicious data, a multiagent system (MAS) that checks commands from the central energy management system is employed. A novel bilevel optimization problem is formulated to model the interaction between the battery and the compromised SPS. A heuristic defense parameter is developed to improve the detection of corrupted commands. The merits of the proposed scheme are evaluated using a risk analysis model. The results of the case studies prove that a combination of autonomous battery with MAS-based heuristic method is effective in mitigating the effects of the cyber attack.