Centralized Dynamic State Estimation Algorithm for Detecting and Distinguishing Faults and Cyber Attacks in Power Systems
Emad Abukhousa, Syed Sohail Feroz Syed Afroz, Fahad Alsaeed, Abdulaziz Qwbaiban, and A.P. Sakis Meliopoulos

TL;DR
This paper presents a centralized Dynamic State Estimation algorithm that effectively detects and distinguishes between cyberattacks and physical faults in power systems, improving grid security and resilience.
Contribution
The study introduces a structured hypothesis testing-based DSE algorithm tailored for microgrids with renewable energy, capable of differentiating cyber and physical anomalies.
Findings
Successfully distinguishes cyberattacks from physical faults in simulations
Enhances reliability and security of power systems against cyber-physical threats
Effective in real-time scenarios with complex anomaly scenarios
Abstract
As power systems evolve with increased integration of renewable energy sources, they become more complex and vulnerable to both cyber and physical threats. This study validates a centralized Dynamic State Estimation (DSE) algorithm designed to enhance the protection of power systems, particularly focusing on microgrids with substantial renewable energy integration. The algorithm utilizing a structured hypothesis testing framework, systematically identifies and differentiates anomalies caused by cyberattacks from those resulting from physical faults. This algorithm was evaluated through four case studies: a False Data Injection Attack (FDIA) via manipulation of Current Transformer (CT) ratios, a single line-to-ground (SLG) fault, and two combined scenarios involving both anomalies. Results from real-time simulations demonstrate that the algorithm effectively distinguishes between…
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Taxonomy
TopicsSmart Grid Security and Resilience · Power Systems Fault Detection · Power System Optimization and Stability
