A Distributionally Robust Defender-Attacker-Defender Model for Resilience Enhancement of Power Systems Against Malicious Cyberattacks

Abstract

The cybersecurity of electric power grids is emerging as a critical challenge for the power industry in the transformation of modern power systems towards the future smart grid. It is of great importance to enhance the resilience of power systems against potential cyber threats. In this paper, a distributionally robust recovery resource allocation method based on the tri-level defender-attacker-defender (D-A-D) model is proposed to enhance the resilience of power systems in the face of malicious cyberattacks. The proposed recovery resource allocation method is able to optimally distribute the recovery resources among the substations in the grid to mitigate the impacts of successful cyberattacks during the recovery process, and improve the resilience performance of power systems against the attacks. In the proposed model, the recovery resource represents the available resource that can be expended to support the recovery efforts of the cyber-physical power system. It is expected to accelerate the recovery process of the system after successful attacks. The recovery resource may include necessary software, hardware, and labor force. Meanwhile, a distributionally robust optimization (DRO) model is proposed to address the uncertainty of the power system operation conditions, e.g., renewable energy resources (RESs). In order to verify the proposed system defense method, case studies were conducted on the IEEE Reliability Test System RTS-79. The results of the case studies show that the proposed method can provide a robust solution to recovery resource allocation for mitigating the risk of potential cyberattacks.