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Convex Relaxations for Severe Damage Analysis in AC Power Networks

Modeling, Computation, Nonlinearity, Randomness and Waves Seminar

Convex Relaxations for Severe Damage Analysis in AC Power Networks
Series: Modeling, Computation, Nonlinearity, Randomness and Waves Seminar
Location: MATH 402
Presenter: Carleton Coffrin, Los Alamos National Labs

The analysis of severe multi-component damage on AC power networks is central to understanding the infrastructure's vulnerability to large-scale natural disasters and coordinated multi-agent attacks.  However, solving the non-convex nonlinear AC power flow equations, after severe network damage, is a challenging task and presents a notable obstacle in vulnerability analysis.  In this work we explore how recent power system analysis methods, based on convex optimization, can be leveraged for severe damage analysis of real-world AC power network datasets.  A rigorous empirical evaluation across seven networks and thousands of damage scenarios demonstrates that convex relaxations of the AC power flow equations can provide a reliable and scalable method for bounding the amount of load shedding required in severe damage scenarios.  Furthermore, this preliminary study suggests that the resilience of different power networks to severe damage scenarios may vary more than previously thought.