Abstract
This project memo documents work carried out on investigating the importance of using dynamic analysis to analyse contingencies that could potentially result in high-impact low-probability (HILP) events. It takes as a starting point a set of potentially critical contingencies in a four-area test network, that were identified in a vulnerability analysis. These potentially critical contingencies were identified on the basis of a quasi-static contingency analysis. Moreover, they depended on assumptions about which parts of the power system might possibly fail to survive a transition to island mode if separated from the rest of the system. The work illustrates how a dynamic analysis improves the understanding of possible sequences of events that could lead to critical consequences. The project memo also includes details on dynamic data included in the four-area test network data set.
