"Dual Graph" and "Random Chemistry" Methods for Cascading Failure Analysis

This paper describes two new approaches to cascading failure analysis in power systems that can combine large amounts of data about cascading blackouts to produce information about the ways that cascades may propagate. In the first, we evaluate methods for representing cascading failure information in the form of a graph. We refer to these graphs as "dual graphs" because the vertices are the transmission lines (the physical links), rather than the more conventional approach of representing power system buses as vertices. Examples of these ideas using the IEEE 30 bus system indicate that the "dual graph" methods can provide useful insight into how cascades propagate. In the second part of the paper we describe a random chemistry algorithm that can search through the enormous space of possible combinations of potential component outages to efficiently find large collections of the most dangerous combinations. This method was applied to a power grid with 2896 transmission branches, and provides insight into component outages that are notably more likely than others to trigger a cascading failure. In the conclusions we discuss potential uses of these methods for power systems planning and operations.