A Data Driven Approach to Robust Event Detection in Smart Grids Based on Random Matrix Theory and Kalman Filtering

Increasing levels of complexity, due to growing volumes renewable generation with an associated influx power electronics, are placing increased demands on the reliable operation modern systems. Consequently, phasor measurement units (PMUs) being rapidly deployed in order further enhance situational awareness for system operators. This paper presents a novel data-driven event detection approach based random matrix theory (RMT) and Kalman filtering. A dynamic filtering technique is proposed condition PMU data. Both simulated real data from transmission Great Britain (GB) utilized validate results show that much more robust regard when applied practical situations.