A PMU-based risk assessment framework for power control systems

Cyber threats are serious concerns for power systems. This paper proposes a risk assessment framework to enhance the resilience of power systems against cyber attacks. The Duality Element Relative Fuzzy Evaluation Method (DERFEM) is used to evaluate quantitatively security vulnerabilities within cyber systems of power systems; the Attack Graph is employed to identify intrusion scenarios that exploit multiple vulnerabilities; an System Stability Monitoring and Response System (SSMARS) is developed to monitor the impact of intrusion scenarios on power system dynamics in real time. SSMARS is a novel PMU application for the Smart Grid. It is designed be implemented in a RTO/ISO control center to assess and enhance power system security on line. SSMARS calculates the Conditional Lyapunov Exponents (CLEs) in real time based on the Phasor Measurement Unit (PMU) data. Power system stability is predicted through the values of CLEs. Control actions based on CLEs are suggested if power system instability is likely to happen. The effectiveness of SSMARS is illustrated with the IEEE 39 bus system model.