CPS- Synergy- Collaborative Research- A Unified System Theoretic Framework for Cyber Attack-Resilient Power Grid
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There is an increased research trend towards the application of distributed control algorithms for network power system control. We analyze the vulnerability of these distributed control algorithms to a potential attack on the communication network. We show that that the decentralized load-side control algorithm for frequency regulation in power system is fragile to communication channel uncertainty. We also propose an optimization-based framework for the design of distributed load-side control algorithm robust to communication channel uncertainty. For problem involving anomaly detection, we describe an online model-based approach to detect cyber-attacks in power system state estimation. The proposed approach leverages information that is independent of traditional SCADA measurements, such as load forecasts, generation schedule information, and existing synchrophasor data to detect measurement anomalies in State Estimators through statistical characterization. An attack scenario where load buses are attacked to cause voltage instability in the system to reduce its performance. Fault Induced Delayed Voltage Recovery (FIDVR) is a phenomenon that can reduce the performance of the component and may induce system-wide instability. An entropy-based method that detects and quantifies this FIDVR phenomenon in real-time from time-series data is developed. The developed method is implemented in a test-bed environment involving Opal-RT and open-Modelica.
Submitted by Umesh Vaidya
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There is an increased research trend towards the application of distributed control algorithms for network power system control. We analyze the vulnerability of these distributed control algorithms to a potential attack on the communication network. We show that that the decentralized load-side control algorithm for frequency regulation in power system is fragile to communication channel uncertainty. We also propose an optimization-based framework for the design of distributed load-side control algorithm robust to communication channel uncertainty. For problem involving anomaly detection, we describe an online model-based approach to detect cyber-attacks in power system state estimation. The proposed approach leverages information that is independent of traditional SCADA measurements, such as load forecasts, generation schedule information, and existing synchrophasor data to detect measurement anomalies in State Estimators through statistical characterization. An attack scenario where load buses are attacked to cause voltage instability in the system to reduce its performance. Fault Induced Delayed Voltage Recovery (FIDVR) is a phenomenon that can reduce the performance of the component and may induce system-wide instability. An entropy-based method that detects and quantifies this FIDVR phenomenon in real-time from time-series data is developed. The developed method is implemented in a test-bed environment involving Opal-RT and open-Modelica.