Research

Distinguishing Between Cyber Attacks and Faults in Power Electronic Systems – A Non-Invasive Approach

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Abstract

With increased cyber infrastructure in large power systems with inverter-based resources (IBRs), it remains highly susceptible to cyber attacks. Reliable and secure operations of such system under a large signal disturbance necessitate an anomaly diagnosis scheme, which is substantial for either selective operation of relays (during grid faults), or cybersecurity (during cyber attacks). This becomes a challenge for power electronic systems, as their characteristic response to such large signal disturbance is very fast. Hence, we accumulate our efforts in this paper to characterize between them accurately within a short time frame. A novel non-invasive anomaly diagnosis mechanism for IBRs is presented, which only requires locally measured voltage and frequency as inputs. Mapping these inputs in a X-Y plane, the characterization process is able to classify between the anomalies within 5 ms. To the best of our knowledge, this mechanism provides the fastest decision in comparison to the existing techniques, which also assists the equipped protection/cybersecurity technology to take corresponding decisions without enforcing any customization. The proposed scheme is validated on many systems using real-time (RT) simulations in OPAL-RT environment with HYPERSIM software and also on a hardware prototype. The results verify the effectiveness, scalability and accuracy of the proposed mechanism under different scenarios.

Anomaly Detection Cyber Attacks Faults Microgrids Non-invasive Power Electronics Power Systems cyber attacks Voltage measurement Anomaly diagnosis Scalability cyber-physical system Inverters Frequency measurement faults Frequency control Reactive power inverters Cyberattack