Physical and Cyber Anomaly Management in Massively Digitized Power Systems

Abstract

The past century has witnessed a digitization trend of electric power grid where increasing digital solutions are being integrated into the grid infrastructure. The digital solutions do not only provide opportunities for enhancing monitoring, control and protection of the power grid, but also pose challenges of ensuring both cyber and physical security of the grid. This dissertation provides three concrete examples in order to leverage the emerging opportunities and to address pressing challenges in massively digitized grid. By using rich streaming synchrophasor data in bulk power transmission systems, a purely data-driven algorithm is proposed in order to locate sources of forced oscillations. To enhance the cyber resilience of the grid, this dissertation develops a theoretically rigorous yet practically implementable method for detecting cyber attacks in Automatic Generation Control. A learning-based framework is designed for assessing physical security of networked microgrids. Furthermore, an advanced Energy Management System for future digitized power grids is envisioned and thereby future research directions are pointed out.