LAUSR

The dramatic increase of cyber-attacks onenergy systems can cause huge losses, which has drawn extensive attention due to the fast integration of information communication technologies (ICTs). This issue is becoming worse with the integration of electricity and gas systems (IEGS), facilitated by gas generation and new coupling technologies. This paper investigates the risk and mitigation strategies for IEGS under false data injection attacks (FDIA) in a hierarchical two-stage framework. The FDIA on both electricity and gas systems are modelled through injecting falsified data by adversaries. To mitigate the adverse impacts, a novel two-stage distributionally robust optimization (DRO) is proposed: i) day-ahead operationto determine initial operationscheme and ii) real-time corrective operation with the realization of FDIA and renewable generation uncertainties. A semidefinite programming is formulated for the original problemand it is then solved by a convex optimization-based algorithm. A typical IEGS is used fordemonstration, which shows that the proposed model is effective in mitigating the risks caused by potential FDIAand renewable uncertainties, by optimal coordinating energy infrastructures and load shedding.This work provides system operators with a powerful toolto operate the IEGS with enhanced security against malicious cyber-attacks while accommodating increasing renewable energy. The method can also be easily extended to operatingIEGS against other natural attacks.