Understanding events for wide-area situational awareness

With synchrophasor-based wide area situational awareness systems, the number of data signals that an operator must process at any given time, especially during disturbances, can be overwhelming. To assist both the operations team as well other teams monitoring and studying the state of the power system, we propose an event understanding framework that processes raw PMU data, generates and represents pertinent event metadata that can be searched and browsed, and derives inferences that can be used to automatically generate reports on important grid behaviors. In this paper, we describe how we detect basic events on the grid and describe an event ontology that provides a vocabulary to categorize these events. We extend this ontology by introducing spatial and temporal relations. As a first use case from post-mortem analysis, we demonstrate how an end user can search for and retrieve event episodes as part of “what if” scenario analysis. As a second use case, we show how to “screen” fault locations with voltage profiles, a base model of the domain, an inference model, and application of a rule-based reasoner. Based on our initial results, we conclude that this is a promising step towards fault localization, and consequently, automatic, post-disturbance report generation.