Topology Robustness of State Estimation Against False Data Injection and Network Parameter Attacks on Power Monitoring and Control Systems

With the integration of information and communication systems, cyberattacks threaten the normal operation of the power grid. As a critical function, state estimation in the power monitoring and control system is an attractive target for attackers. There are two typical cyberattacks—false data injection attack (FDIA) and network parameter attack (NPA)—that produce incorrect state estimation results, threatening the control and operation of the power system. This paper introduces the first theoretical framework for analyzing the topology robustness of state estimation against FDIA, NPA, and coordinated FDIA+NPA, quantifying the inherent tolerance to injected errors under the DC model. Novel contributions include the following: (1) derivation of analytical bounds on relative state errors for FDIA and similar expressions for NPA and coordinated attacks; (2) proof that sensor measurements, network topology, and branch parameters are key factors influencing robustness, with larger robustness factor amplifying errors in dense or partially measured systems; and (3) validation through extensive MATPOWER simulations on IEEE 14-, 30-, 57-, 118-, and 300-bus systems, confirming bound tightness across scales. These insights enable preventive grid design to enhance resilience against cyber-physical threats.