Role of thermal effects in blackout probabilistic risk assessment

The blackout risk in power systems is difficult to estimate by actual probabilistic methods because they usually neglect, or do not properly consider, the dependencies between failures and the dynamic evolution of the grid in the course of a transient. Our purpose is therefore to develop an integrated probabilistic approach to blackout analysis, capable of handling the coupling between events in cascading failure, and the dynamic response of the grid to stochastic initiating perturbations. This approach is adapted from dynamic reliability methodologies. This paper focuses on the modeling adopted for the first phase of a blackout, ruled by thermal transients. The goal is to identify underestimated dangerous cascading scenarios and better calculate their frequency. A Monte Carlo code specifically developed for this purpose is validated on a test grid. Some dangerous scenarios are presented and their frequency calculated by this method is compared with a classical estimation, showing important differences.