Distinguishing Between Cyber Attacks and Faults in Power Electronic Systems—A Noninvasive Approach
Kirti Gupta, Subham Sahoo, Rabindra Mohanty, Bijaya Ketan Panigrahi, Frede Blaabjerg
Abstract
With the increased cyberinfrastructure in large power systems with inverter-based resources (IBRs), it remains highly susceptible to cyber-attacks. Reliable and secure operations of such a 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 disturbances is very fast. Hence, we accumulate our efforts in this article to characterize them accurately within a short time frame. A novel noninvasive anomaly diagnosis mechanism for IBRs is presented, which only requires locally measured voltage and frequency as inputs. Mapping these inputs in a <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$XY$ </tex-math></inline-formula> -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.