A graphical approach to quickest outage localization in power grids

Line outage detection and localization play pivotal roles in contingency analysis, power flow optimization, and situational awareness delivery in power grids. Hence, agile detection and localization of line outages enhance the efficiency of operations and their resilience against cascading failures. This paper proposes a stochastic graphical framework for localizing line outage events. This framework capitalizes on the correlation among the measurements generated across the grid, where the correlation is induced by the connectivity topology of the grid. By formalizing a proper correlation model, this paper designs data-adaptive coupled data-acquisition and decision-making processes for the quickest localization of the line outages. This leads to efficient outage localization by partially observing the grid and is shown to outperform the existing dimensionality reduction methods.