A Bi-Level Model for Detecting and Correcting Parameter Cyber-Attacks in Power System State Estimation

Power system state estimation is an important component of the status and healthiness underlying electric power grid real-time monitoring. However, such a prone to cyber-physical attacks. The majority research in systems security focuses on detecting measurements False-Data Injection While this important, measurement model parameters are also most part process. Measurement though, known as static-data, not monitored real-life applications. solutions ultimately provide estimated states. A state-of-the-art presents two-step process towards simultaneous false-data injection security: detection correction. Detection steps χ2 statistical hypothesis test based, while correction consider augmented vector approach. In addition, step uses iterative solution relaxed non-linear with no guarantee optimal solution. This paper linear programming method detect correct cyber-attacks parameters. presented bi-level integrates steps. Temporal spatio characteristics used online tool for attacks pertaining model. implemented IEEE 118 bus system. Comparative results highlight improved accuracy. An easy-to-implement model, built classical weighted least squares solution, without hard-to-derive parameters, highlights potential aspects